ACTAUNIVERSITATIS

UPSALIENSISUPPSALA

2017

Digital Comprehensive Summaries of Uppsala Dissertationsfrom the Faculty of Science and Technology 1610

Three-component digital-basedseismic landstreamer

Methodologies for infrastructure planningapplications

BOJAN BRODIC

ISSN 1651-6214ISBN 978-91-513-0186-0urn:nbn:se:uu:diva-335846

Dissertation presented at Uppsala University to be publicly examined in Hambergsalen,Geocentrum, Villavagen 16, Uppsala, Friday, 2 February 2018 at 10:00 for the degree ofDoctor of Philosophy. The examination will be conducted in English. Faculty examiner: Dr.André Pugin (Natural Resources Canada – Near Surface Geophysics).

AbstractBrodic, B. 2017. Three-component digital-based seismic landstreamer. Methodologiesfor infrastructure planning applications. Digital Comprehensive Summaries of UppsalaDissertations from the Faculty of Science and Technology 1610. 80 pp. Uppsala: ActaUniversitatis Upsaliensis. ISBN 978-91-513-0186-0.

To support urban infrastructure planning projects, along with various other near-surfaceapplications, a multicomponent landstreamer was developed. The landstreamer was builtwith broadband (0-800 Hz), three-component (3C) micro-electro-mechanical system (MEMS)sensors. The digital nature of the MEMS sensors makes the developed landstreamer insensitiveto electric/electromagnetic noise.

The landstreamer’s design and its seismic imaging capabilities, along with the MEMStechnical specifications, were evaluated in several studies. When comparing signals recordedwith the streamer with planted MEMS sensors, no negative effects of the design were noted.Compared to different geophones tested, the streamer produced higher quality and broadersignal bandwidth data. Additionally, a seismic study conducted in a tunnel demonstratedits electric/electromagnetic noise insensitivity. The streamer combined with wireless seismicrecorders was used to survey logistically challenging areas for improved imaging andcharacterizations and avoid interference with traffic.

For example, at the Stockholm Bypass site, the landstreamer recorded data were used fortraveltime tomography with results showing a well delineated bedrock level and potentiallow-velocity zones matching with inferred poor-quality-class rocks. The seismic response offractures and their extent between a tunnel and the surface was studied at the Äspö Hard RockLaboratory site. The velocity model obtained using the traveltime tomography approach showedknown well-characterized fracture systems and potential additional formerly unknown ones.Additionally, compressional- and shear-wave velocities, seismic quality factors, Vp/Vs anddynamic Poisson’s ratios of the known fracture zones were obtained. Fractures and/or weaknesszones in the bedrock were imaged using refraction and reflection imaging methods at a sitecontaminated with a cancerogenic pollutant in southwest Sweden, illustrating the potential ofthe streamer for environmental-related applications. In southern Finland, the landstreamer wasused for SH-wave reflection seismic imaging from a vertically oriented impact source withthe results showing a well-delineated bedrock level and weak reflections correlating well withgeology. At the same site, its potential for multichannel analysis of surface waves (MASW) wasdemonstrated. The surface-wave obtained shear-wave velocities match well with the boreholebased stratigraphy of the site and are complementary to the SH-wave reflectivity and previousinvestigations at the site.

Studies conducted in this thesis demonstrate the landstreamer’s potential for various near-surface applications and show the benefits and need for 3C seismic data recording.

Keywords: landstreamer, multicomponent seismic, shear-waves, surface-waves

Bojan Brodic, Department of Earth Sciences, Geophysics, Villav. 16, Uppsala University,SE-75236 Uppsala, Sweden.

© Bojan Brodic 2017

ISSN 1651-6214ISBN 978-91-513-0186-0urn:nbn:se:uu:diva-335846 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-335846)

To my family and friends

Supervisor Professor Alireza Malehmir Department of Earth Sciences – Geophysics Program Uppsala University Co-supervisor Professor Christopher Juhlin Department of Earth Sciences – Geophysics Program Uppsala University Faculty examiner Dr. André Pugin Natural Resources Canada – Near Surface Geophysics Ottawa Committee members Associate Professor Beatriz Benjumea Moreno Department of Geodynamics and Geophysics University of Barcelona Associate Professor Michal Malinowski Institute of Geophysics Polish Academy of Sciences, Warsaw Dr. Cedric Schmelzbach Department of Earth Sciences – Institute of Geophysics ETH Zürich

List of Papers

This thesis is based on the following papers, which are referred to in the text by their Roman numerals.

I Brodic, B., Malehmir, A., Juhlin, C., Dynesius, L., Bastani, M., & Palm, H. (2015). Multicomponent broadband digital-based seismic landstreamer for near-surface applications. Journal of Applied Geophysics, 123, 227–241.

II Brodic, B., Malehmir, A., & Juhlin, C. (2017a). Delineating fracture zones using surface-tunnel-surface seismic data, P-S and S-P mode conversions. Journal of Geophysical Research: Solid Earth, (122), 5493–5516.

III Brodic, B., Malehmir, A., Bastani, M., Mehta, S., Juhlin, C., Lundberg, E., & Wang, S. (2017b). Multi-component digital-based seismic landstreamer and boat-towed radio-magnetotelluric acquisition systems for improved subsurface characterization in the urban environment. First Break, 35(8), 41–47.

IV Brodic, B., Malehmir, A., & Maries, G. (2017c). 3C seismic landstreamer study of an esker architecture through shear- and surface-wave imaging. Submitted to Geophysics.

Reprints were made with permission from the respective publishers. Addi-tionally, during the course of my PhD work, I have contributed to the follow-ing papers that are not included in this thesis.

Brodic, B., Malehmir, A., & Juhlin, C. (2017). Bedrock and Fracture Zone Delineation Using Different Near-surface Seismic Sources. In 23rd Europe-an Meeting of Environmental and Engineering Geophysics. – extended ab-stract.

Malehmir, A., Wang, S., Lamminen, J., Brodic, B., Bastani, M., Vaittinen, K., Juhlin, C., & Place, J. (2015), Delineating structures controlling sand-stone-hosted base-metal deposits using high-resolution multicomponent seismic and radio-magnetotelluric methods: A case study from northern Sweden, Geophysical Prospecting, 63(4), 774–797.

Malehmir, A., Zhang, F., Dehghannejad, M., Lundberg, E., Döse, C., Friberg, O., Brodic, B., Place, J., Svensson, M., & Möller, H. (2015), Plan-ning of urban underground infrastructure using a broadband seismic land-streamer - Tomography results and uncertainty quantifications from a case study in southwestern Sweden, Geophysics, 80(6), B177–B192.

Malehmir, A., Andersson, M., Mehta, S., Brodic, B., Munier, R., Place, J., Maries, G., Smith, C., Kamm, J., Bastani, M., & Mikko, H. (2016), Post-glacial reactivation of the Bollnäs fault, central Sweden; a multidisciplinary geophysical investigation, Solid Earth, 7(2), 509–527.

Contributions

Papers included in the thesis are a result of collaboration with different indi-viduals, throughout different stages of survey design, acquisition, discus-sions and manuscript preparation.

For Paper I, I participated in the streamer assembly and data acquisition campaigns, wrote the initial version of the manuscript, conducted the anal-yses, refraction tomography and prepared most of the figures. My co-authors helped by preparing the 3D visualization, doing the finite-difference model-ing, commenting and correcting through numerous stages of the text evolu-tion until its publication.

For Paper II, I was part of the experiment design, data acquisition, conduct-ed all the analyses, prepared the figures and wrote an initial version of the manuscript. Discussions during the design and analysis stage along with a number of text iterations by the co-authors resulted in its published form.

Paper III, was a joint endeavor of different individuals, some of which are listed as co-authors, while the others were acknowledged in the text. I pre-pared the figures, conducted the tomography and wrote the initial version of the manuscript. The co-authors provided the stacked section, RMT results and helped by significantly improving the original text.

For Paper IV, I participated in the data acquisition part, conducted all the analyses and processing, prepared the final figures and wrote the first manu-script. My co-authors provided the P-wave stacked section and refraction tomography results, and improved the text via a number of iterations.

Contents

1 Introduction ......................................................................................... 13 1.1 Seismic landstreamer for complex subsurface characterization ......... 14 1.2 MEMS-based landstreamer and outline of the thesis ......................... 16

2 Seismic waves ...................................................................................... 19 2.1 Elasticity, P- and S-wave velocities ................................................... 20

3 Seismic methods .................................................................................. 22 3.1 Elements of active seismics and data acquisition ............................... 22 3.2 Seismic receivers ................................................................................ 25

3.2.1 Geophones .................................................................................. 26 3.2.1.1 Geophones, application and considerations ........................ 28

3.2.2 MEMS-based technology and landstreamer sensors .................. 28 3.2.2.1 MEMS sensors, applications and considerations ................ 31

4 Three-component MEMS-based landstreamer - configuration ........... 33

5 Summary of papers .............................................................................. 35 5.1 Paper I: Multicomponent broadband digital-based seismic landstreamer for near-surface applications ............................................... 35

5.1.1 Summary ..................................................................................... 35 5.1.2 Conclusions ................................................................................ 40

5.2 Paper II: Delineating fracture zones using surface-tunnel-surface seismic data, P-S, and S-P mode conversions .......................................... 41

5.2.1 Summary ..................................................................................... 41 5.2.2 Conclusions ................................................................................ 49

5.3 Paper III: Multi-component digital-based seismic landstreamer and boat-towed radio-magnetotelluric acquisition systems for improved subsurface characterization in the urban environment ............................. 50

5.3.1 Summary ..................................................................................... 50 5.3.2 Conclusions ................................................................................ 53

5.4 Paper IV: 3C seismic landstreamer study of an esker architecture through shear- and surface-wave imaging ................................................ 54

5.4.1 Summary ..................................................................................... 54 5.4.2 Conclusions ................................................................................ 61

6 Conclusions and outlook ...................................................................... 63

Summary in Swedish .................................................................................... 66

Acknowledgments......................................................................................... 69

References ..................................................................................................... 71

Abbreviations and acronyms

1C Single component 3C Three component 3D Three-dimensional MEMS Micro-electro-mechanical system TRUST Transparent Underground Structures km Kilometer m Meter Hz Hertz kg Kilogram Vp Compressional wave velocity Vs Shear-wave velocity EM Electromagnetic Qp Vp seismic quality factor Qs Vs seismic quality factor RMT Radio-magnetotelluric s Second ms Millisecond CMP Common-midpoint dB Decibel MASW Multichannel analysis of surface waves

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1 Introduction

Since the beginning of the Industrial Revolution in the late 18th century, the human population has rapidly been increasing from less than a billion, to about 7.5 billion at present (United Nations, 2017). The population burst has resulted in accelerated urban expansion, increasing the need for energy and resources and causing changes of the environment (Liu and Chan, 2007). It has been estimated that less than 30% of the world’s population lived in the cities 50 years ago, while the numbers have reached more than 50% nowa-days (Liu and Chan, 2007; United Nations, 1988). With the present urbani-zation and population expansion rates, it is estimated that by 2025, out of projected world population of 8.3 billion, more than 60% will be city dwell-ers (Liu and Chan, 2007; United Nations, 1988; World Economic Forum, 2016). As the population density increases, the movement of people and volume of goods through highly developed areas would require greater speed, resulting in greater need for new and modern infrastructure, both above and beneath the surface. This will in turn place an increasing stress on resources and existing infrastructure and magnify community problems such as soil and ground contamination by toxic pollutants, landslides and/or ground subsidence due to water extraction (Henderson, 1992). Therefore, great need exists to improve our understanding and develop new methods for better characterization of the shallow subsurface geological conditions (Henderson, 1992).

Although direct observations (drilling, trenching and/or excavations) pro-vide in-situ information of the subsurface, they are cumbersome, expensive and sometimes logistically difficult or even impossible. Additionally, the information obtained in this manner may be looked upon as “needle sticks” and representative of only a rather small volume around the sampled zone (Svensson, 2006). However, continuous information over larger areas, along with their non-invasive nature, brought focus on geophysical methods due to their attractiveness for near-surface site characterization since the early 1990s (Henderson, 1992).

Near-surface characterization using geophysical methods can be a rather challenging task, particularly in urban and mining environments. Operating in these environments, apart from the natural noises (wind, rain, waves, etc.), generally involves a large amount of anthropogenic noise sources such as electric, magnetic and/or electromagnetic (EM) interference from cables, power lines, buried pipes and fences, or vibrational noise from railway and

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tram lines, traffic, among others (Fenning et al., 1994; Henderson, 1992; Liu and Chan, 2007; Miller, 2013). Existing infrastructure and traffic impose additional operating space and time restrictions, requiring the equipment to be versatile, low disruptive and easy to deploy and pick up (Henderson, 1992; Malehmir et al., 2014; Miller, 2013). In addition to the aforemen-tioned, the subsurface strata may be complex and disturbed by infilling ma-terials or covered by asphalt and paved surfaces making the coupling of geo-physical sensors a difficult task (Fenning et al., 1994; Henderson, 1992). Regardless of the difficulties, if correctly designed and implemented, geo-physical methods are capable of providing essential information and detailed images of subsurface structures for infrastructure planning, site characteriza-tions, mine development and exploration, among others (Dehghannejad et al., 2017; Malehmir et al., 2015a, 2015c, 2017a).

1.1 Seismic landstreamer for complex subsurface characterization To cope with the continuously evolving challenges of geophysical site char-acterization in complex environments, as the principal objective of this the-sis, I dealt with the development and testing of a prototype, state-of-the-art, three-component (3C) seismic landstreamer. The landstreamer can be de-fined as an array of seismic receivers that can be pulled along the ground without the need for “planting” (Inazaki, 1999; van der Veen and Green, 1998). The concept of a towed land cable with the receivers coupled to the ground by their own, or the weight of the receiver holders (sledges), dates back to mid-1970s (Kruppenbach and Bedenbender, 1975). Although, from both economical and practical points of view, the concept of pulling the en-tire seismic spread, instead of manually planting geophones and connecting them to cables was attractive, it was not until the end of 1980s when the early application came in the form of a snow-streamer (Determann et al., 1988; Eiken et al., 1989). With establishment of the 24-bit recording equip-ment and modern processing algorithms towards the end of the 1990s, the landstreamers found a more permanent place in the world of seismic investi-gations (Inazaki, 1999; Pugin et al., 2004b; van der Veen et al., 2001; van der Veen and Green, 1998). This decreased the man-power necessary, hence the cost, and increased the seismic data acquisition rates significantly (Pugin et al., 2004a). Following these pioneering works, seismic landstreamers of different designs have demonstrated their value for subsurface characteriza-tion in various settings, particularly on asphalt and paved urban environment (Brodic et al., 2015; Huggins, 2004; Inazaki, 2004; Krawczyk et al., 2013; Malehmir et al., 2015c; Pilecki et al., 2017; Polom et al., 2013; Pugin et al., 2004a, 2013c).

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Single component (1C) landstreamers have successfully been utilized for compressional-, shear- and surface-wave imaging of the subsurface in vari-ous settings (Almholt et al., 2013; Boiero et al., 2013; Hayashi and Inazaki, 2006; Huggins, 2004; Inazaki, 1999, 2004, 2006, Ivanov et al., 2006, 2009, Krawczyk et al., 2012, 2013; Link et al., 2006; Malehmir et al., 2013; Pilecki et al., 2017; Polom et al., 2013; Pugin et al., 2004a; Pullan et al., 2008; Svensson, 2006; van der Veen et al., 2001; Wisén et al., 2012). In addition to these, although not as numerous, studies have been reported involving multi-component landstreamers for contaminated site mapping and natural hazard studies (Hunter et al., 2010; Martinez et al., 2012), aquifer delineation (Mar-tinez et al., 2010; Pugin et al., 2009, 2013a, 2013c), urban studies (Almholt et al., 2011; Pugin et al., 2004a, 2013b; Wisén et al., 2012), comparison with 3C planted geophones (Stewart, 2009; Suarez and Stewart, 2008) and shal-low hydrocarbon detection (Duchesne et al., 2016).

All the aforementioned studies have been conducted with landstreamers whose design involved different types of geophones (e.g., vertical, horizon-tal, gimbaled and/or omnidirectional; for more details see Brodic et al. (2015), Huggins (2004) and Pilecki et al. (2017)). Even though geophones are relatively small and light, reliable, robust and require no power to oper-ate, their mechanical nature imposes certain restrictions. Some of them in-clude electrical or EM noise pickup, limited bandwidth and reduced ampli-tude response due to tilting, among others (Hons et al., 2007; Meunier, 2011; Mougenot, 2004). Compared to the geophone-based landstreamers men-tioned, the prototype seismic landstreamer developed at Uppsala University, the topic of my thesis, is built with digital 3C, MEMS-based (microelectro-mechanical system) sensors. Since the original assembly that took place in July 2013 (discussed in Paper I), it has successfully been used at numerous sites in Sweden, Finland, Norway and Denmark. Table 1.1 shows the sites, survey goals and corresponding reported studies.

The work presented in my thesis was primarily supported and undertaken under the umbrella of a nationwide, industry-academia consortium, Trans-parent Underground Structures (TRUST GeoInfra; www.trust-geoinfra.se) project. Sub-project TRUST 2.2, led by Uppsala University, was established with the aim of developing modern seismic and electromagnetic instruments and methods for better planning of underground infrastructure projects in the urban environment. As a result, a boat-towed RMT (radio-magnetotelluric; Bastani et al. (2015), Mehta (2017), Wang et al. (2017)) system and the seismic landstreamer, described in detail in this thesis, were developed. The goals behind the landstreamer were to develop a proto-type system that is relatively portable and can easily be deployed or picked up, pulled by an ordinary car (relatively light), combined with geophones and wireless re-corders using the same recording system, that enables 3C broadband record-

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ing for a variety of applications, and more importantly, insensitive to elec-tric/EM noise pickup dominant in urban environment.

Table 1.1 Sites and survey goals where the developed landstreamer has so far been used. Sweden:

• Laisvall (October 2013): Mineral exploration and geological mapping (Malehmir et al., 2015b)

• Stockholm (November 2013): Förbifart Stockholm, site characterization and equipment quality control (Brodic et al., 2015 - Paper I)

• Kristianstad (April 2014): Contaminated site mapping (Brodic et al., 2017b - Paper III) • Varberg (May 2014): Planning of a double-track train tunnel (Dehghannejad et al.,

2017; Malehmir et al., 2015c) • Bollnäs (October 2014): Post-glacial fault imaging and characterization (Malehmir et

al., 2016) • Äspö (April 2015): Tunnel-surface-tunnel and landstreamer seismics for fracture map-

ping (Brodic et al., 2017a - Paper II) • Ludvika (October 2015): Mineral exploration and geological site mapping (Malehmir et

al., 2017a) • Mora (October 2015): Sub-surface geological mapping (Muhamad et al., 2017). • Malmberget (Nov 2015): Mapping hazardous zones due to mining activities (Juhlin et

al., 2017) • Marsta (January 2017): Bedrock and fracture zone imaging using different seismic

sources – ongoing work • Varberg (June 2017): Structural controls in mobilization of contaminants and remedia-

tion planning prior to start of the tunneling – ongoing work Norway:

• Oslo (June 2015): Planning of the E18-Oslo tunnel (Bazin et al., 2016) Finland:

• Turku (July 2014): Seismic imaging of esker architecture and water management (Mar-ies et al., 2017; and Paper IV)

• Siilinjärvi (July 2014): Mineral exploration/mine planning (Malehmir et al., 2017b) Denmark:

• Copenhagen (May 2015): Chalk group mapping at Stevns peninsula and PhD training course (Kammann et al., 2016)

1.2 MEMS-based landstreamer and outline of the thesis The thesis consists of 7 chapters, including Chapter 1 where the background to the topic and the thesis objectives are given. In Chapter 2, I briefly review the fundamentals of seismic waves, wave velocities in subsurface media and why both compressional and shear waves should be recorded and analyzed. In Chapter 3, I provide an overview of the basics behind seismic data acqui-sition, with a particular focus on seismic receivers and differences between geophones and MEMS-based sensors. Chapter 4 introduces the landstreamer assembly and its present configuration. Finally, in Chapter 5 the findings of the five articles contained in the second part of the thesis are summarized. Two following chapters (Chapter 6 and 7) summarize the contributions of

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the articles and the thesis itself, in English and Swedish, respectively. The articles included address both applied and technical aspects of the developed landstreamer.

Apart from the practical, Paper I and Paper II have a strong technical as-pect and the issues raised in them are related to:

• Comparison between signals recorded with MEMS-based sensors mounted on the landstreamer versus planted geophones (vertical, 10 Hz and 28 Hz natural frequency, 7 cm spike);

• Comparison between streamer-mounted versus planted MEMS sensors to show no unwanted effects of the streamer assembly;

• Testing the streamer properties inside a tunnel and demonstrating the electric/EM noise insensitivity of the MEMS sensors;

• Combination of different types of wireless seismic recorders (1C vertical geophones, 3C MEMS-based) with the landstreamer to provide data in inaccessible areas and simultaneous data acquisi-tion on the surface and inside a tunnel.

All the papers in this thesis also address certain practical aspects of interest for both the local and general scientific community. In Paper I, the first urban study with the 3C, MEMS-based landstreamer was done in one of the Stockholm suburbs at a site belonging to a 21-km long, multi-lane motor-way, tunnel project (Stockholm Bypass - Förbifart Stockholm). The study was conducted at one of the access tunnels, presently under construction, with the aim to delineate bedrock surface and potential weakness zones. Here, the landstreamer coupled with wireless seismic recorders and a sledgehammer was used along two nearly perpendicular seismic profiles. The first break traveltime tomography results obtained showed a reasonable match with drilled depth to bedrock and indicated potential locations of weakness zones.

Paper II shows the combination of planted vertical geophones, landstreamer and wireless seismic recorders, with the landstreamer located inside a tunnel approximately 200 m below the surface. The implemented approach was successful in characterizing the rock mass and fracture systems between the tunnel and the surface, using first break traveltime tomography. It may be applied during the tunnel excavation phase to monitor changes in rock quali-ty due to the excavation and opens up possibilities for in-mine seismic stud-ies. Additionally, it addresses the in-situ characterization of open fractures with different degrees of fluid saturation in the hard rock environment and their effect on seismic wave propagation. The fractures were characterized by their compressional and shear-wave velocities (Vp and Vs), seismic quali-

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ty factors1 of both (Qp and Qs) and their dynamic Poisson’s ratio, at wave-lengths of field seismic experiments. To the best of my knowledge, this is the only available reported study with simultaneous recording of the seismic wavefield at the surface and inside the tunnel.

Paper III was a joint endeavor to introduce the two systems developed with-in TRUST 2.2 to a broader audience, and I will focus only on the land-streamer part of it in my thesis. The landstreamer was used on a site contam-inated with chlorinated hydrocarbons to map potential fractures in the bed-rock that can be used as migration pathways for the contaminants. Both P-wave reflection and refraction seismics were successful in imaging bedrock and potential fractures or weakness zones. Additionally, the results show a good correlation with other geophysical methods applied at the site and re-ported independently by other teams (Lumetzberger, 2014).

In previous articles, focus of the applied part was on the vertical component data of the 3C landstreamer. However, this left the other two components (horizontal radial and transverse) largely underutilized. Therefore, Paper IV deals with shear-wave seismic imaging using the horizontal transverse com-ponent to image bedrock level and esker architecture at a site in southwest-ern Finland. Since the source used in this study was a vertical impact drop-hammer, clear reflections in the horizontal transverse (SH-wave) component made it rather unusual and worth to study in detail. The reflections were analyzed to confirm their SH-wave nature and processed to obtain a final reflection seismic stacked section for imaging purposes. The results indicate a well-delineated bedrock and show weak events related to the glacial sedi-mentation history of the site. In addition, this is the first publication showing the potential of the MEMS-based landstreamer for surface-wave analysis. Due to survey design limitations, the surface-wave analysis was done on the vertical component data. Both shear-wave velocities and Vp/Vs ratios in the top 40 m were obtained, matching well with P- and SH-wave reflectivity and borehole based stratigraphy of the site, confirming interpretations conducted independently using P-wave first break traveltime tomography and reflection seismics (Maries et al., 2017).

1 The inverse of seismic quality factor is the seismic wave attenuation.

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2 Seismic waves

A seismic wave can be defined as a propagation of an elastic disturbance through the media (Sheriff, 2002). Seismic waves can propagate through the subsurface in the form of compressional (primary or P-wave) or shear (sec-ondary or S-wave) waves. Primary and secondary waves travel at different velocities, with P-wave being faster than the S-wave, and they are non-dispersive. The non-dispersive nature implies that all frequency components in a wave train propagate with the same velocity. In addition to these, in a bounded elastic media (e.g., free surface, weathering layer and bedrock), two distinct types of waves can travel between the boundary and the free surface and are referred to as surface waves. These are Rayleigh and Love waves and both are guided and dispersive waves. Compared to the Rayleigh wave whose propagation only requires a bounded elastic media, the Love wave occurs if the shear-wave velocity above the boundary is lower than the un-derlying layer (Kearey et al., 2002).

All the aforementioned waves propagate with different particle motions. In an isotropic media, the particle motion of the P-wave is parallel to the propagation direction, while the passing S-wave induces particle motions perpendicular to the propagation direction (Pujol, 2003). An S-wave can be further subdivided into two distinct modes, the SH- and the SV-waves. In an anisotropic media, if the shear-wave enters at an oblique angle with respect to the anisotropy plane, a phenomenon called shear-wave splitting2 may occur (Hardage et al., 2011). Since in all papers making the core of this the-sis, except Paper III, I have dealt with analysis of particle polarization (hodograms3), Figure 2.1 illustrates the idealized case of P- and S-wave vec-tors with respect to the wave front and particle motions of the two, along with surface-wave particle motions. We can note from the figure that P-, SV- and SH-wave vectors are normal to each other.

2 In an anisotropic media, under favorable conditions, shear wave splits into fast and slow components, with the faster one generally propagating parallel to the plane of foliation, frac-tures, tectonic stresses or mineral orientation, while the slower one propagates perpendicular to it. 3 A hodogram is defined as a display of the particle path or plot of a motion of a point as a function of time (Sheriff, 2002).

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Figure 2.1. Illustration of the P- and S-wave vectors, with S-wave subdivided into vertical (SV) and horizontal (SH) components relative to the wave front shown in grey. Direction of particle motions for individual body wave are indicated with dashed arrows and the dashed ellipse and half ellipse schematically show planes and trajectories of the particle motions of Love (L) and Rayleigh (R) surface waves. The angle between S- and SV-wave vectors is called the S-wave polarization angle.

2.1 Elasticity, P- and S-wave velocities When a seismic wave propagates through the subsurface, the wave induced stresses result in temporary strain (or deformation) of the media. The result-ing strains associated with the seismic pulse are minute and may be consid-ered elastic4 (Dentith and Mudge, 2014; Kearey et al., 2002). The response of the media to wave induced strains is connected to its elastic constants that also govern the seismic wave velocities.

Assuming linear elasticity, Hooke's law can be used to obtain a relation-ship between elastic constants and compressional- and shear-wave velocities. Although the relationship is a fourth-order tensor, it can be written as:

=

=

zx

yz

xy

zz

yy

xx

zx

yz

xy

zz

yy

xx

CCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCCC

εεεεεε

σσσσσσ

666564636261

565554535251

464544434241

363534333231

262524232221

161514131211

, (2.1)

with directionally dependent stresses (σ), strains (ε) and Cnn the respective elastic constants. Depending on the complexity of the materials, we can dis- 4 In the source’s immediate vicinity, the deformation may be plastic (Dentith and Mudge, 2014)

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tinguish isotropic, transversely isotropic, orthorhombic, monoclinic and tri-clinic classes of symmetry (Thomsen, 1986 and 2002). Different symmetry classes mandate the number of elastic constants necessary to characterize a media and for the isotropic case, only two constants are needed and the P- and S-wave velocities (Vp and Vs, respectively) in this type of media are:

ρμ

ρ3/411 +== KCVp and

ρμ

ρ== 44CVs , (2.2)

where, ρ represents the density, while K and µ are the bulk and the shear moduli, respectively.

Practically, the two equations above indicate that compressional- and shear-waves are sensitive to different rock properties. P-wave velocity is essential-ly dependent on three factors: density, shear- and bulk-moduli. It is highly sensitive to the rock fluid content due to the sensitivity of the bulk modulus to fluid compressibility (Dvorkin, 2001; Mukerji and Mavko, 1994). Since the P-wave velocity is dually dependent on fluid compressibility and shear moduli, P-waves can propagate in both liquids and solids. However, the shear-wave velocity depends on the density and the shear modulus of the media, hence it is relatively insensitive to fluid content and the shear-wave can propagate only in solids (Garotta, 1999). Compared to the P-wave, the shear-wave velocity and reflectivity depend only to a minor degree on the fluid or gas content in a formation (Garotta, 1999).

Combining the information from P- and S-waves, a better and more con-strained data interpretation is achieved. Some of the benefits and examples may involve Vp/Vs ratios that are often used as a lithology indicator and to map structures with different gas or fluid content (Castagna et al., 1985; Johnston and Christensen, 1993; Tsuneyama et al., 2003). The Vp/Vs ratio was also used in Paper IV to confirm the previously conducted interpreta-tion and shows an excellent correlation with the stratigraphy of the site and indicates a clear water-table boundary. Others, such as the Poisson’s ratio and dynamic shear modulus are important for geomechanical purposes and geotechnical site characterization (Krawczyk et al., 2013; Mohamed et al., 2013; Salem, 2000). Additionally, the lower velocity nature of the S- com-pared to the P-wave usually provides higher resolution seismic sections, hence enabling more detailed interpretation of the subsurface (Krawczyk et al., 2013; Malehmir et al., 2013; Polom et al., 2013; Pugin et al., 2004b). Another important property of the shear waves is their higher sensitivity to azimuthal anisotropy and fracture intensity, making their polarization and splitting a natural tool to investigate the two phenomena and the tectonic evolution of a site (Garotta, 1999; Hardage et al., 2011; Paterson and Wong, 2005).

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3 Seismic methods

Seismic methods are used to image the subsurface structures encountered by a traversing seismic wave and observed at the surface or in a borehole (Sher-iff, 2002). As it propagates through the subsurface, seismic wave energy may reflect from structures with different impedance5 contrasts, refract from higher velocity structures or diffract from subsurface discontinuities such as dykes or faults (Sheriff, 2002). After being subjected to any of these phe-nomena, a portion of the energy is dissipated due to geometrical spreading, scattering and/or attenuation, while a portion returns to the surface (or bore-hole) receivers where the arrival times of different waves at different source offsets is recorded (Dentith and Mudge, 2014; Drijkoningen and Verschuur, 2003; Kearey et al., 2002; Sheriff and Geldart, 1995). With almost a century of usage, different seismic methods have successfully been applied for vari-ous purposes, from crustal scales (e.g., Moho imaging; Prodehl et al. (2013)) to imaging structures shallower than 3 m (e.g., Baker et al. (2000)). Alt-hough passive seismic methods6 are attracting more attention, the lower fre-quencies of the earth’s natural sources, or ambient noise, still make them inferior in comparison to controlled-source (active) seismic experiments (Bensen et al., 2007; Draganov and Ruigrok, 2015; Hanssen, 2011; Hanssen and Bussat, 2008; Kapotas et al., 2003).

3.1 Elements of active seismics and data acquisition In an onshore active-source seismic experiment, seismic waves are excited by a seismic source (e.g., sledgehammer, vibrator, weight drop, explosives, etc.) and the resulting ground motion detected by an array of seismic receiv-ers is transferred and saved on to a recording unit. The ground’s response to source induced energy, as a function of time from the source energy onset,

5 Acoustic impedance is a product of density of the media and its seismic velocity (Sheriff, 2002). 6 With regards to the source nature, passive seismic methods can be divided into natural seis-micity methods, such as daylight imaging (DLI; e.g., Claerbout, 1968; Draganov and Ruigrok, 2015) and local earthquake tomography (LET; e.g., Kapotas et al., 2003; Martakis et al., 2012). Methods using ocean waves, e.g. sea-floor compliance (SFC; Crawford and Singh, 2008); and microseism surface wave methods, e.g. ambient noise tomography (ANT; e.g., Bensen et al., 2007, 2008) and surface-wave amplitudes (SWA; e.g., Gorbatikov et al., 2008).

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detected by a single receiver comprises a time series called a seismogram or a seismic trace (Dentith and Mudge, 2014). Since reflection seismic experi-ments commonly involve 10s, 100s or even 1000s of receivers, the recorded seismograms may be displayed and analyzed in different domains. Most common ways to analyze seismic data is via inspection of source or shot gathers (plot of seismic traces as a function of distance from the source - offset); receiver gathers (plot of seismic traces recorded by a single receiver from different sources, typically also as a function of offset) and common midpoint (CMP) gathers (plot of traces having the same midpoint – the point midway between source and receiver), among others (for details and other data domains, see Meunier (2011)). Elements of the data acquisition, with propagation paths of different seismic waves and an example source gather are shown in Figure 3.1.

Figure 3.1. Seismic data acquisition with propagation paths of different seismic waves/rays illustrated on a two-layer model (left) and an example source gather showing arrival times of different waves to the receivers located along the profile (right). “R” represents the seismic receivers, while different colored lines show different seismic events; green – direct wave, light blue – surface wave, dark blue – refracted wave and red – paths of reflected waves. Note that the surface wave occurs in the zone between two light blue lines. Sound wave is not that evident on the source gather.

Distribution of receivers and sources in a seismic survey makes a “seismic spread” (Dentith and Mudge, 2014). We can distinguish 2D, limited or sparse (swath) 3D and full 3D acquisition spreads. With 2D spreads, sources and receivers are located along a 2D profile (as used in all the papers of this thesis). Limited or sparse 3D spreads have sources and receivers arranged in such way that a pseudo 3D target illumination (e.g., Hedin et al. (2016)) or swath 3D imaging (e.g., Malehmir et al. (2009)) is possible. In a 3D spread, receivers are arranged along a grid and sources distributed to obtain equal fold and receiver-source offset-azimuth coverage (e.g., Ashton et al. (1994)). Typically, 2D seismic data are acquired using fixed spreads (fixed receiver position, source moves along the seismic profile; Papers II and III, Stock-

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holm Bypass study of Paper I), split-spread and end-on spread geometry (e.g., Stone (1994)). However, since the landstreamer has a fixed number of receivers along its length, different acquisition techniques can be used. In the Stockholm Bypass study of Paper I, which is also the most commonly used technique at Uppsala University presently, the landstreamer was fixed along the first position and the source moved until the data were acquired along the entire streamer length. The streamer then moves forward, until an overlap of 20 stations (80 m) with the previous position is reached. Following this, the source continues 4 m away from the last shot location of the first land-streamer position. The towing vehicle is also used as the recording vehicle. The overlap prevents loss of data coverage between succeeding streamer positions. Entire procedure is illustrated in Figure 3.2a, while Figure 3.2b illustrates the preferred technique for MASW that is also common with re-ported landstreamer studies (Boiero et al., 2013; Ivanov et al., 2009; Kraw-czyk et al., 2012; Pilecki et al., 2017; Pugin et al., 2009, 2013c). For the latter, the source is also used as a recording vehicle and, for every new shot, the landstreamer is pulled to the next position with a source increment of Δx.

Figure 3.2. Different landstreamer data acquisition strategies. (a) Streamer is fixed and the source moves until the data are acquired along its entire length. Following this, the streamer moves forward, until an overlap of 20 stations with the previous position is obtained, and the source continues 4 m away from the last shot position. Pulling vehicle is also the recording vehicle. (b) For every new shot position, the entire landstreamer is pulled forward by a distance Δx, until entire planned profile length is surveyed. The source acts here as a recording vehicle. “S” denotes source and “R” receiver.

Regardless of the technique, reflection seismic surveys are designed to have good and constant multiplicity of common-midpoints (fold) in the target

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zone, while the MASW studies aim for a constant or mid-spread7 point cov-erage along the entire profile.

3.2 Seismic receivers A seismic receiver is a device used to measure the ground movement when it is shaken by a perturbation and translates it into voltage (Havskov and Al-guacil, 2016). We can distinguish motion sensors in which the receiver’s output signal is proportional to displacement, velocity (velocimeters - geo-phones) or acceleration (accelerometers), and pressure sensors (e.g., hydro-phones) sensitive to pressure changes (Meunier, 2011). Receiver selection strongly depends on the survey goals dictating whether we are interested in ground motion detection along one or several axes (1C or 3C, even 4C) and the frequency band of interest. However, the receiver’s output signal de-pends on the characteristics such as frequency response, sensitivity, dynamic range, sensor linearity, cross axis sensitivity, and nowadays, power con-sumption and available static and dynamic tests (Havskov and Alguacil, 2016).

The frequency response of a sensor relates to its design in having a flat velocity or acceleration response within the desired frequency range (Havskov and Alguacil, 2016). For geophones, this range is typically bound-ed by the natural frequency8 on the lower, and the spurious frequency9 on the higher frequency end. The resonance frequency is often damped to provide a stable frequency response using a manufacturer specific damping factor10. This factor is related to the stiffness of the springs opposing the movement of the moving mass, hence slowing down the oscillations to provide a more stable output (Maxwell, 2014). Practically, although the resonant frequency is the lower limit, the signal is still retrievable down to about 70% below it (Bertram et al., 1999; Ivanov et al., 2008).

The sensitivity of a receiver relates to the smallest ground movement that can be translated into useful signal and is specified by the manufacturer in volts per unit of velocity or acceleration (Havskov and Alguacil, 2016; Li et al., 2009). It is connected to the coil resistance, number of its wire turns and the resulting magnetic flux intensity. As the coil resistance increases, so do 7 Mid-spread point in an MASW survey corresponds to the location of a 1D shear-wave ve-locity profile obtained from inverting the surface-wave dispersion curve. 8 The resonance frequency of the spring-mass system is called the natural frequency and below it, the amplitude response decreases significantly. 9 At frequencies above spurious, the resonance of the spring-mass system perpendicular to its working axis occurs, resulting in multiple vibration modes (Faber and Maxwell, 1996). These frequencies occur about 10 to 20 times the natural frequency (Maxwell, 2014). 10 The damping factor mandates if the spring/mass system of the sensor will oscillate or not. We can distinguish underdamped (less than 1, oscillating), critically damped (1, minimal damping to prevent oscillations) and overdamped (grater then 1, non-oscillating) systems.

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the sensitivity and the self-noise, hence a compromise between the two has to be made (Havskov and Alguacil, 2016).

The sensor’s dynamic range is the ratio of the highest and lowest signal that can be detected and is expressed in units of dB as:

)/log(20)( aAdBrangedynamic = , (3.1)

with A being the largest and a the smallest signal detected (Dragašević, 1983; Gadallah and Fisher, 2005).

Linearity indicates that the sensor should behave as a linear system, for example if the input is doubled, so will be the output. However, this is often not specified by the manufacturer and a good sensor has a linearity of about 1% or better (Havskov and Alguacil, 2016).

Cross axis sensitivity of the sensor (crosstalk) tells us how will large am-plitudes on the measuring component of a 3C sensor influence the other two components. Typically it is below 2%, and sensors with feedback systems have a much better linearity and cross axis sensitivity (Havskov and Algua-cil, 2016).

Seismic experiments nowadays involve a large number of receivers, therefore power consumption and field tests, e.g., ground coupling, crosstalk, leakage, tilt, among others, play an important role. The analog sensors, alt-hough requiring no power to operate, provide less testing abilities and the analog-to-digital (A/D) conversion (either at field digitizing units – FDU’s or the recording system itself) leaves plenty of space for electric and EM noise pickup. In comparison to them, the output signal of the digital sensors is digital, but need to be powered in order to detect the ground motion and provide output signal.

3.2.1 Geophones Geophones are the most commonly used devices in seismic exploration and, with more than 6 million produced per year, still dominate the seismic mar-ket (Meunier, 2011). They are made using different designs, with the typical one involving a moving-coil system (Figure 3.3).

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Figure 3.3. Elements of a typically used geophone (left) with a cross-section illus-trating moving-coil system (right). A propagating seismic wave causes ground mo-tion, hence respective movement of the geophone to the ground surface. This results in a relative movement of the inertial mass in the magnetic field of the stable magnet along the coil axis, producing the output signal. Modified after Linear Collider Con-sortium (www.linearcollider.org).

The moving coil is suspended by springs from the field of a permanent mag-net attached to the geophone casing. The entire system is placed in a geo-phone casing that is fixed to the ground by a spike as shown in Figure 3.3. The suspended coil, permanent magnet, is an oscillatory system with mass of the coil and the stiffness of suspension springs determining its resonance frequency. The geophone’s output voltage is proportional to the seismic wave velocity and depends on the natural and spurious frequency, sensitivity and the damping factor (Kearey et al., 2002). Typical geophones have a damping constant of 0.7, enabling flat frequency response above the natural frequency (Kearey et al., 2002; Li et al., 2009; Meunier, 2011; Sheriff, 2002). They are small, robust and reliable, requiring no power to operate, and sense the motion along the coil’s axis (e.g., vertical and/or horizontal geophones). The number of coils, along with their orientation defines the number of components (1C, 2C or 3C), or 4C when combined with a pres-sure sensor.

The output of the oscillatory system is related via geophone’s transfer function to its input, where the frequency-velocity response function (Av) in the frequency domain can have the form (Havskov and Ottemoller, 2010):

( ) 20

222220

2

4)

ωωhωω

Gω=(ωAv+−

. (3.2)

Here, G is the sensitivity, h damping constant, ω angular frequency and ω0=2πf0, with f0 the geophone’s resonance frequency. The amplitude is given by the real, while the phase by the imaginary part of the spectrum.

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3.2.1.1 Geophones, application and considerations Although seismic surveys are designed with their specific goals, it is not uncommon, particularly in urban and near-surface studies, that the seismic data are used for various types of analyses. However, this is where the me-chanical nature of geophones may introduce limitations.

The limited frequency bandwidth of geophones may become problem if seismic reflection and refraction, surface-wave analysis, passive noise stud-ies or even full-waveform inversion studies are to be done on the same da-taset. As discussed in Paper I of this thesis, either low-frequencies are sacri-ficed, by choosing geophones of high natural frequencies, to obtain high-resolution seismic sections, or low-frequency geophones are used for full-waveform inversions or surface-wave analysis to limit high-frequency con-taminations.

Unless omnidirectional geophones11 are used, geophones have to be care-fully planted for tilting to be avoided. Most of the available geophone speci-fication sheets have tilt angle tolerances of 5-15°, with lower natural fre-quency geophones being more sensitive to tilt. The output amplitude of a geophone is proportional to the cosine angle from the vertical (e.g., for a geophone planted 20° from vertical, there is a 5% loss in amplitudes; Gadal-lah and Fisher (2005)). Although omnidirectional geophones do not suffer from this issue, their relatively high resonant frequency (~30 Hz and above) limits their usage in the low frequency band.

As shown in Paper II of this thesis, the greatest challenge in urban seis-mic exploration using geophones is the electric or EM noise pickup. Since geophones are mechanical devices, output voltage caused by the ground motions has to be translated into digital form for further analysis. Regardless of where the A/D conversion takes place, it leaves space and potential for electric/EM noise pickup. Paper II demonstrates that the geophone data are contaminated, despite the A/D being only a meter away, not just by the elec-tric power grid frequency, but also its lower and higher order harmonics and the difficulty to suppress them entirely. However, the MEMS-based sensors used in the same study are unaffected from this noise.

3.2.2 MEMS-based technology and landstreamer sensors To build a seismic data acquisition system that will overcome the aforemen-tioned limitations, a decision was made to design the landstreamer with MEMS-based instead of coil-based sensors. The “MEMS” stands for micro-electro-mechanical-system (different varieties of the name can be found in literature) and it was introduced to the seismic industry in in late 1990s

11 Geophones with higher natural frequency (greater than ~30 Hz) are considered as omnidi-rectional. They tend to have stiffer springs and can work in various orientations (Maxwell, 2014).

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(Maxwell, 1999). Since then, different companies have made commercially available, either 1C or 3C, MEMS-based seismic sensors (Gibson et al., 2005; Hall et al., 2010; Hons et al., 2007; Meunier, 2011; Milligan et al., 2011). For the landstreamer introduced in this thesis, Sercel DSU3TM (3C) sensors were used. The choice of sensor was based on earlier experience and compatibility with the existing acquisition system at Uppsala University. Additionally, an important part was the possibility to combine MEMS- and geophone-based sensors, along with wireless recorders of both types, using only one acquisition system. I will here briefly describe the operational prin-ciples behind MEMS-based sensors, taking the DSU3 as an example, and discuss some of their advantages and drawbacks compared to geophones.

Three-component digital sensor units (DSU3) are tri-axial, MEMS-based seismic sensors with a wide diameter spike as shown in Figure 3.4a and a digital output signal. Similar to coil-mass system, when subjected to ground movement, the MEMS sensor casing motion results in displacement of the reference mass (Figure 3.4b). This displacement is annulated by the digital feedback system, with the output proportional to the correction force neces-sary to keep the mass movement negligible when ground is accelerated (Meunier, 2011). A micro-machined thin piece of silicon, on both sides cov-ered with metal plating, acts as the moving mass and mobile electrodes. The frame holding the mass represents the transducer part and together with the moving mass forms a capacitor. The capacitance change is registered by an ASIC (application specific integrated circuit) that transfers mass displace-ment into voltage proportional to wave acceleration (Hons et al., 2007, 2008; Laine and Mougenot, 2014). Very thin regions of silicon, suspending the mass from the frame and allowing nanometer scale motions, represent the mechanical concept of springs (Figure 3.4b). The spring-frame-moving mass system has a resonant frequency above 1000 Hz (Hons, 2008).

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Figure 3.4. Three-component MEMS-based sensor (DSU3TM) used on the land-streamer. (a) A close up of the DSU3 with cuts through the outer coating showing the inner electronic parts. Photo by A. Malehmir 2014. (b) Simplified version of the internal components of MEMS-ASIC circuits. Modified after Laine and Mougenot, (2014).

In comparison to geophones, the MEMS-based sensor transfer function is a frequency-acceleration function (Aa) whose derivation involves contributions of both the force feedback system and the frame-reference mass. Without going into derivations, the MEMS transfer function, according to Hons et al. (2007) can be defined as:

0

9.81)ω

G(A aa =ω , (3.3)

where ω0 represents the MEMS resonant frequency (1000 Hz) in rad, and Ga the sensitivity of the MEMS sensor. If necessary, to convert from response of a MEMS to a geophone response, an equation scaling the MEMS accel-erometer output by a scaling factor of the following form can be used (Hons et al., 2007):

( ) 20

222220

2

4

81.9)()

ωωhωω

ωG

G=A

(ωAaa

v

+−ω, (3.4)

with the same terminology used here as for the geophone transfer function. While geophones are designed to operate above their natural frequency

(e.g., 10 Hz) and give an analog signal as output, the MEMS sensors are designed to operate below their natural frequency (e.g., 1000 Hz) and the output is digital. Apart from the digital output, theoretically the DSU3 MEMS sensors have a stable frequency response with no signal attenuation from 0 to 800 Hz (Mougenot and Thorburn, 2004), making them a valuable receiver for different seismic studies. The high resonant frequency also ena-

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bles retrieval of tilt of all three axes with an inbuilt DSU3 test function measuring the direct current related to the gravity acceleration. Values of the gravity vector can be used later to correct for the tilt of the individual com-ponents (or applied automatically) and sensitivity calibration (Gibson et al., 2005; Kendall, 2006; Mougenot and Thorburn, 2004).

3.2.2.1 MEMS sensors, applications and considerations MEMS-sensors have been on the market for almost 20 years. During this period they have gained a lot of popularity and are used in every “smartphone” nowadays (Kong et al., 2016). However, judging by the re-ported studies, their usage in seismic exploration is an almost negligible percent of the amount of data acquired using geophones (Brodic et al., 2017a; Donati et al., 2016; Jianming et al., 2008; Malehmir et al., 2015b, 2016, 2017b, 2017a; Maries et al., 2017; Stotter and Angerer, 2011; Tellier and Lainé, 2017). Whether this is due to their higher price compared to geo-phones, wider diameter spike making the planting more time consuming, claims that they are less sensitive to lower frequencies (Hons, 2008; Laine and Mougenot, 2014; Meunier, 2011), or any other factors remains to be studied in detail. Table 3.1 provides a summary based on reported studies and specifications for different geophones and MEMS sensors. Parameters and values shown in the table are based on: frequency bandwidth (Laine and Mougenot, 2014; Li et al., 2009), tilt tolerance (Gibson et al., 2005; Li et al., 2009), dynamic range (Gibson and Burnett, 2005; Li et al., 2009), S/N ratio (Hons, 2008; Laine and Mougenot, 2014; Lawton et al., 2006), sensitivity to EM noise and power consumption (Li et al., 2009).

Table 3.1. Differences between MEMS sensors on the landstreamer and typical geophone-based acquisition system.

Parameter Streamer MEMS sensors Average geophone

Frequncy bandwith 0-800 Hz 10-400 Hz Dynamic range 120 dB 70 dB S/N ratio

<10 Hz Lower Higher 10 – 50 Hz Similar Simmilar >50 Hz Higher Lower

Tilt angle tolerance Vertical componet 57° 25° Horizontal components 27° 5°

Tilt angle measured Yes No Ability to resist EM noise Strong Weak Signal output Digital Analog Power consumption 400 mW 420 mW Price per channel 1000 $ 100 $

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Judging from Table 3.1, the landstreamer MEMS sensors consume less pow-er, have a higher tilt angle tolerance and a broader frequency bandwidth. Regarding the tilt angle, from my own perspective, the numbers shown are likely an overestimate. The real advantage of MEMS versus geophones, with respect to tilting, is the ability to measure the tilt angles of all three compo-nents of any unit. This enables an interactive control and the possibility to either physically straighten the unit, or correct its amplitude response using the measured tilt angle. Studies such as by Laine and Mougenot (2014), Li et al. (2009) or Hons (2008) claim that below 10 Hz, the noise floor of the DSU3 can exceed the ambient noise level, where geophones may be more appropriate than MEMS sensors. In the articles making the core of this the-sis, I have not seen that effect. However, in all of the studies presented in the articles, the geophones used alongside the landstreamer had a resonant fre-quency of either 10 Hz or 28 Hz. Additionally, apart from the surface-wave analysis in Paper IV, none of the studies were focused on the low frequency part of the landstreamer datasets. In June 2017, I participated in a study where 24 DSU3 sensors connected to wireless recorders were used, along with 560 vertical spike-type geophones of 4.5 Hz resonant frequency, along a ca. 600 km long wide-angle seismic refraction profile. Although Moho reflections were noted on the DSU3 sensors used, compared with the 4.5 Hz geophones, the frequency response of DSU3 sensors was poorer for frequen-cies below 10 Hz (S. Buntin, 2017, personal communication). This claim remains to be tested in the future with more low-frequency studies (e.g., surface waves, active or passive) and side-by-side comparison with lower natural frequency geophones.

In summary, no electric/EM pickup, broadband signal, numerous test capa-bilities and 3C recording, make the DSU3 MEMS-based sensors, coupled with the landstreamer, a valuable tool for high-resolution reflection and re-fraction seismic studies, along with other studies involving low frequencies, e.g., surface-wave analysis (Brodic et al., 2015, 2017a, 2017b; Dehghan-nejad et al., 2017; Malehmir et al., 2015b, 2016, 2017b, 2017a; Maries et al., 2017).

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4 Three-component MEMS-based landstreamer - configuration

The articles included in this thesis give an overview of the streamer’s evolu-tion since the original assembly in June 2013. In this chapter I will make a review of the design, with respect to the present configuration, and short comparisons with reported landstreamer studies (e.g., Ivanov et al. (2009), Krawczyk et al. (2012), Pilecki et al. (2017), Pugin et al. (2013a)). The pre-sent configuration of the landstreamer consists of 100 DSU3TM (MEMS-based) sensors mounted on 5 different segments connected by small trolleys carrying line powering units. Every segment has 20 sensors mounted on sensor holders (sledges) and the entire sensor-sledge assembly weighs ap-proximately 5 kg. A great amount of time was invested in designing the sledges to keep the center of the mass as low as possible and engineering the materials holding the sensor. The sledges are connected by high-endurance, non-stretchable cargo straps. Four segments have sensors spaced at 2 m, while the fifth one has sensors 4 m spaced, making the spread 240 m long. The entire design was made to have the system as light as possible to be towed by an ordinary car (or an ATV), while still being heavy enough to provide good sensor-ground coupling. Table 4.1 shows a comparison of the landstreamer discussed in my thesis, with existing landstreamers and Figure 4.1 shows different elements of the landstreamer design.

Table 4.1 Comparison between technical specifications of commonly available land-streamers and the one discussed in this thesis. Parameters MEMS landstreamer Existing landstreamers Sensor type 3C MEMS-based Geophones (1C or 3C) Frequency bandwidth 0 - 800 Hz 4.5 ~ 400 Hz Tilt measurement Recorded in the header Not possible Acquisition system Sercel Lite (MEMS +

geophones) Most commonly Geometrics Geode (geophones only)

Max number of channels 1000 24 (per unit) Sensor spacing 2 - 4 m 0.75 – 2 m Cabling Single Several Data transmission Digital Analog Data format SEGD SEG2 GPS time Recorded in the header Often not possible

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Figure 4.1. Different elements of the landstreamer design. (a) One segment with 2 m unit spacing pulled by a car. (b) Sensor-sled assembly with the internal coordinate system of the sensor. Every sensor has a “north arrow” mark. (c) Trolley connecting different landstreamer segments and carrying a power unit.

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5 Summary of papers

5.1 Paper I: Multicomponent broadband digital-based seismic landstreamer for near-surface applications The landstreamer was designed with the primary objectives to be versatile, easily combined with other types of receivers (either geophones or wireless seismic recorders), provide 3C broad bandwidth recording, along with elec-tric/EM noise insensitivity. All these objectives were put on a test in three studies conducted at the early stage of the landstreamer development. Two studies were of a technical nature where the landstreamer recorded signal was compared with data recorded with different geophones and MEMS-based sensors of the same type. This was done for quality control purposes to check if the landstreamer assembly introduces any serious change on the recorded signal and to compare the landstreamer recorded signal with differ-ent vertical-type geophones to check its reliability and claimed advantages. The third study in this paper represents the first urban study conducted with the landstreamer. The study aimed at testing the electric/EM noise insensitiv-ity of the landstreamer sensors, along with identification of bedrock level and weakness zones along two seismic profiles at one of the planned access tunnels of the Förbifart Stockholm.

5.1.1 Summary To validate the capabilities and reliability of the newly developed system in an early development stage, one segment consisting of 20 MEMS sensors spaced 2 m, was compared side-by-side with two planted seismic lines hav-ing 20 vertical spike-type geophones. One line had geophones with a natural frequency of 10 Hz, while the other had 28 Hz natural frequency geophones. As illustrated in Figure 5.1a, the landstreamer was located in between the two geophone lines with the geophones planted approximately 25 cm away from the nearest landstreamer sensor. The test was conducted along a bicycle road in the backyard of Department of Earth Sciences, Uppsala University. The same recording system was used to simultaneously record all three seismic lines with a sampling rate of 0.5 ms and a 5-kg sledgehammer strik-ing an aluminum plate was used as the seismic source.

An additional test was conducted at a test site in Finland with 12 DSU3 sensors planted next to 12 landstreamer sensors (Figure 5.1b) to test if the

36

sledges introduced any negative effect. Here, a 500-kg Bobcat mounted drop hammer was used as the seismic source, hitting next to the nearest land-streamer station. The same acquisition system was used to simultaneously record the data on all sensors with a sampling rate of 1 ms.

Figure 5.1. Photos showing the two studies conducted to test the capabilities and reliability of the developed landstreamer. (a) Layout of the three seismic lines com-pared in the study, left (28 Hz geophones), right (10 Hz geophones). (b) Side-by-side comparison of planted versus DSU3 sensors on the landstreamer.

Since the landstreamer sensors are accelerometers, while the geophones rec-ord data in the velocity domain (Hons, 2008; Lawton et al., 2006), the land-streamer data were transferred to velocity domain via integration for com-parison purposes as shown in Figure 5.1a,. Figure 5.2 shows source gathers of the landstreamer versus two geophone-based seismic line tests, after verti-cal stacking of four repeated records to increase the S/N ratio. Also shown are the corresponding amplitude spectra, normalized to the highest amplitude (Figure 5.2f) and without normalization – raw amplitudes (Figure 5.2g). The amplitude spectra of the landstreamer’s vertical component are shown both before and after integration (red and green lines in Figure 5.2f,g, respective-ly). The vertical component data of the landstreamer show better quality than those of the geophones, judging by the hyperbolic event shown with the red arrow (Figure 5.2c). This event is significantly weaker on the 10 Hz geo-phone data (Figure 5.2a), while it is completely absent on the 28 Hz geo-phone data (Figure 5.2b). Data recorded with two horizontal components (Figure 5.2d – horizontal inline; Figure 5.2e – horizontal crossline) are also shown, with the crossline component indicating traces of what appears like a mode converted event shown with a red arrow. The amplitude spectra shown in Figure 5.2f,g indicates a broader frequency bandwidth of the landstreamer sensors, both before and after integration. This is particularly notable on the

37

raw amplitude spectra shown in Figure 5.2g, with a higher S/N ratio in the high-frequency end.

Figure 5.2. Side-by-side comparison of landstreamer recorded data versus two planted seismic lines with vertical 10 Hz and 28 Hz geophones, along with the corresponding amplitude spectra. Source gathers recorded with (a) 10 Hz vertical geophones, (b) 28 Hz vertical geophones, (c) vertical component of the land-streamer sensors, (d) horizontal inline, and (e) crossline components. Note that the landstreamer sensor data (MEMS accelerometers) were integrated to match the velocity domain of geophones. (f and g) Show the normalized and raw amplitude spectra, respectively. For plotting purposes of source gathers, trace normalization was applied.

Figure 5.3 shows a side-by-side comparison of corresponding trace pairs of planted (red) and landstreamer mounted (black) DSU3 sensors for the verti-cal and two horizontal components, with the corresponding amplitude spec-tra. Also shown are particle motion analysis (hodograms) of channel one (indicated by red and black arrows) for different planes and windows repre-senting the ambient noise, first arrivals and later arrivals. What can be noted on trace pairs of both vertical and horizontal inline components is almost identical waveforms and similar patterns on hodograms of both planted and streamer mounted DSU3 sensors. Amplitude spectra of the aforesaid com-

38

ponents appear similar, with differences more notable over 300 Hz. The largest difference can be noted on the horizontal crossline component, with some of the trace-pairs indicating phase-shifted waveforms. Differences may also be noted on particle motions and partly amplitude spectra of the same component. Judging by the almost identical nature of the vertical and hori-zontal crossline components, the differences seen are rather due to wind, ambient noise or different ground coupling, than the landstreamer design itself, that appears to introduce no unwanted effect. As shown in Figure 5.1b, the planted DSU3 sensors were placed in a hole and covered by loose mate-rials, making different coupling of individual trace pairs and likely contrib-uting the overall difference.

Figure 5.3. Side-by-side comparison of trace pairs corresponding to landstreamer mounted (black) and planted (red) DSU3 sensors. Upper portion corresponds to trace pairs of the individual components (vertical, horizontal inline and crossline) with corresponding amplitude spectra. Lower part of the figure shows particle mo-tion plots for different plains of the trace pair indicated by black and red arrows, within windows corresponding to noise, first breaks and later arrivals. For plotting purpose, trace normalization has been applied and different gains were used to en-hance different particle motion plots.

To test the landstreamer performance in an urban environment and charac-terize the bedrock and inferred poor rock class zones, two seismic profiles were acquired in Stockholm, Sweden. The site belongs to one of the access tunnels of the 21-km long multilane underground motorway project (Stock-holm Bypass or Förbifart Stockholm). The location of two profiles acquired

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in this study (Lines 1 and 2), along with field photos, is shown in Figure 5.4. At the time of acquisition (November 2013), the streamer had 3 segments. Two segments had 20 units spaced at 2 m, while the third one had 20 units spaced 4 m. Due to heavy road traffic and trams going every 10 min until late in the night, both lines were acquired during night hours. A sledgeham-mer striking an aluminum plate was used as the seismic source with source points spaced every 2 m along both lines. Line 1 was acquired with 5 moves of the landstreamer, leaving the segment with 4 m unit spacing to overlap with the previous streamer position, as explained in Chapter 3. Total length of it was about 550 m. Line 2 was logistically more demanding due to severe topographic variations and a major road crossing it. Not to interfere with the traffic along the road, and still obtain data coverage under it, the landstream-er was combined with wireless seismic recorders using the same type of MEMS sensors. Six wireless units were deployed along both roadsides. Af-ter acquiring the data in the NE part, the streamer was moved across the road and the data acquisition continued. This time, only two segments with sen-sors spaced 2 m were used and 3 streamer moves made, without any overlap with the previous position. This resulted in a 400 m long seismic line.

Figure 5.4. Overview of the site conditions and positions of the two seismic profiles acquired at one of the access tunnels of the Stockholm Bypass project. (a) Positions of seismic profiles acquired (Line 1 and 2) on top of color-coded elevation map, along with projections of tunnel track and access ramp with colors representing different quality rocks. (b) Photo showing the NW end of Line2. (c) Photo showing the major road in the middle of Line 2, tram passing next to it, along with arrows pointing at wireless units used not to interfere with the traffic and still obtain data coverage under the road.

Only the vertical component of the landstreamer-recorded data was ana-lyzed, and, even though Line 2 was going parallel to the tram tracks, no elec-tric/EM noise pickup was observed. After the finite difference modeling showed the site geology to be unfavorable towards reflection seismic imag-ing, 3D first break refraction traveltime tomography was done on the vertical component data. For this purpose, the ps_tomo code (Tryggvason et al.,

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2002) was used with cell size of 2 m in all directions and RMS errors of about 3 ms were obtained. The tomography results along both lines, along with the tunnel model and aerial photo projected on top of the elevation model are shown in Figure 5.5. The results indicate a good delineated bed-rock corresponding well with the mapped outcrops and low velocity zones correlating relatively well with the previously inferred poor class rock zones.

Figure 5.5. (a) Aerial photo projected on top of the elevation model showing posi-tion of the two seismic profiles (Lines 1 and 2), along with location of bedrock out-crops. (b and c) Traveltime tomography results along both profiles with tunnel track and access ramp models shown from different angles.

5.1.2 Conclusions For quality control purposes, the potential of a newly developed 3C MEMS-based seismic landstreamer was examined in a number of tests. The initial tests included a side-by-side comparison against two planted seismic lines with 28 Hz and 10 Hz vertical spike-type geophones, respectively. The test results indicate a better quality data of the landstreamer, judging by a reflec-tion that appears to be the most pronounced in the vertical component of the streamer, while it is rather weak on 10 Hz and absent on 28 Hz geophone lines. Amplitude spectra of the streamer data indicate a much broader band-width than the geophones tested. Additionally, another side-by-side test was done by comparing planted units of the same type as used on the streamer versus the streamer mounted ones. The results indicate that the streamer assembly introduces no unwanted effects on the recorded data of the vertical and horizontal inline component. The horizontal crossline component shows some differences, likely due to different ground coupling. An urban study was also conducted to test the electrical/EM insensitivity of the landstreamer

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sensors and image the bedrock and previously inferred poor class rocks. Two seismic profiles were acquired along one of the access ramps of the Stock-holm Bypass. The obtained refraction tomography results match well with bedrock outcrops, drilled depth to bedrock and indicate low-velocity zones with poor class rocks.

5.2 Paper II: Delineating fracture zones using surface-tunnel-surface seismic data, P-S, and S-P mode conversions To test the landstreamer recording properties inside a rock mass, it was de-ployed in a tunnel at approximately 160 m below the surface, along a zone where two large scale, steeply dipping fracture zones intersect the tunnel. The test was conducted at the Äspö HRL (Hard Rock Laboratory), an under-ground research facility in SE Sweden. To obtain an overview of the rock mass and fracture systems between the surface and the tunnel, the land-streamer was coupled with vertical geophones in the tunnel, and wireless seismic recorders on the surface. One of the survey goals involved simulta-neous data recording in the tunnel and on the surface and tomography imag-ing of the rock mass in-between the two. Other goals were focused on ana-lyzing the landstreamer data and its imaging capabilities of fractures with different degrees of hydraulic conductivity in a hard rock environment, along with their seismic response.

5.2.1 Summary The Äspö HRL consists of several research facilities on the surface and ap-proximately 3.6 km of tunnels at different depths. From the surface entrance, at about 15 m above sea level, the main tunnel goes for approximately 1.6 km downwards to the level of 230 m below sea level. After this, it spirally continues downwards until the final depth of - 450 m. Different tunnel levels are connected to the main building on the surface via an elevator shaft. The tunnel was excavated in granitic-granodioritic rocks with numerous, both local and regional scale, fractures and fracture systems intersected (Berglund et al., 2003). Since the late 1980s, different geological, hydrological, geome-chanical and geophysical studies, among others, were used to describe the properties of the aforementioned tectonic features and the rocks hosting them (Berglund et al., 2003; Stanfors et al., 1999). Figure 5.6 shows the tun-nel model with an aerial photo projected on top of the elevation model and the position of different seismic receivers used in the experiment.

Starting approximately 50 m away from the tunnel entrance, 279 vertical spike-type geophones (10 Hz natural frequency) were planted on the side of

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the tunnel (Geophones I arrow in Figure 5.6). The geophones were placed firmly in drillholes spaced at 4 m. Following this, the landstreamer was de-ployed on the edge of the asphalt on the tunnel floor (Landstreamer arrow in Figure 5.6). At the time of acquisition (April 2015), the streamer had 4 seg-ments, 3 with 20 sensors spaced 2 m and one with 20 sensors 4 m apart. Due to its 3C nature, it was deployed along the tunnel part where two large scale, steeply dipping fracture systems (NE-1 and EW-3) intersect the tunnel. Where the tunnel intersects the fractures, NE-1 is approximately 80 m wide with three subsets (NE-1-I to NE-1-III) of different widths separated by less fractured host rocks. Earlier site studies have described the first two, NE-1-I and II, as highly fractured and clay altered with the latter being more hydrau-lically conductive than the former (Berglund et al., 2003). The third set, the NE-1-III, is described as fractured and highly hydraulically conductive (Ber-glund et al., 2003). Following the last unit of the landstreamer, 54 vertical, spike-type geophones, were placed in drillholes at the tunnel side with 4 m spacing (Geophones II arrow in Figure 5.6). This provided an approximately 1.5 km long seismic line in the tunnel.

Figure 5.6. Tunnel model with aerial photo projected on top of the elevation model, with different seismic receivers and their positions indicated by arrows and the re-cording vehicle position.

The surface part was covered with 75 wireless seismic recorders (labeled Wireless in Figure 5.6), both connected to 10 Hz vertical geophones and the same sensors as on the landstreamer. Wireless recorders were planted with 8 - 16 m unit spacing. In the sea above the tunnel, an independent marine seismic experiment (Ronczka et al., 2016) was simultaneously conducted (Marine experiment arrow in Figure 5.6). Part of the receivers used in that experiment were merged with our datasets and used for analysis. A Sercel LiteTM was used to record the data and a 500-kg vertical impact drophammer as the seismic source (Place et al., 2015; Sopher et al., 2014). Since the re-cording system requires GPS time to operate, the recording vehicle was placed outside the tunnel (Recording vehicle arrow in Figure 5.6). Using the GPS time as a common reference, simultaneous data recording inside the

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tunnel and on all surface receivers was achieved. At the bottom of the source’s hammer casing, a large metal plate was mounted and inside the tunnel, the source was used with station spacing of 4 – 16 m. At every source point, the weight was released 5 times onto the base plate and the individual hits used later for vertical stacking and improving the S/N ratio. At the sur-face, the source was used along all the accessible locations.

Example raw source gathers of all the receivers inside the tunnel, along with individual components of the landstreamer are shown in Figure 5.7. What can be noted from Figure 5.7a is the severe electric/EM noise contam-ination of both parts of the seismic line with planted geophones (Geophones I and II), while the landstreamer appears entirely free of it (Figure 5.7b,c,d). Apart from the main 50 Hz current frequency, both higher and lower order harmonics can be seen on the amplitude spectra of the geophones, while nothing is observed on the landstreamer part. Prominent side noise coming likely from the nuclear power plant in the site’s vicinity can also be seen (side noise trains arrow in Figure 5.7a).

Figure 5.7. Example raw source gathers from the receivers located inside the tunnel. (a) Mixed receiver source gather with geophones planted before the landstreamer (Geophones I), the landstreamer portion of the seismic line (DSU3’s landstreamer) and geophones planted after the streamer (Geophones II). Different components of the landstreamer; (b) vertical, (c) horizontal inline and (d) horizontal crossline en-larged to demonstrate the landstreamer sensors insensitivity to electric/EM noise contamination.

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After a few iterations of frequency filtering, the noise is mostly attenuated as shown in Figure 5.8, with strong first arrivals of both P- and S-waves. What was also notable in the raw data, and became more pronounced after filter-ing, were strong mode converted events likely originating from the two frac-ture systems intersected by the landstreamer. Figure 5.8a shows the mode-converted events (both direct and reflected P-S and S-P mode converted waves) in the vicinity of the NE-1 and Figure 5.8b showing the events in the vicinity of the EW-3 fracture system. Both 2D finite difference modeling (Juhlin, 1995) and 3D constant velocity raytracing traveltime modeling (Ayarza et al., 2000) were later used and the obtained results indicate that the mode converted events originate from the aforementioned fracture systems.

Figure 5.8. Filtered shot gathers illustrating mode converted and reflected events in the vicinity of the NE-1 (a) and the EW3 (b) fracture systems. The inset in (a) shows an enlarged view of the events and a delay of first arrivals when the seismic wave intersects NE-1 fracture system. Note the strong nature of both P- and S-wave direct arrivals.

The strong nature of both P- and S-wave direct arrivals was exploited and used for joint P- and S-wave first arrival traveltime tomography. Both P- and S-wave first arrivals were picked for all surface and tunnel sources and re-ceivers. This resulted in 67,690 P- and 64,540 S-wave first arrivals from 230 sources recorded on 528 receivers. The tomography was done in 3D space

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using the ps_tomo traveltime tomography code (Tryggvason et al., 2002) with a 4 m cell size in the inline and depth directions. A crossline cell size of 200 m was used (to obtain a 2D velocity slice incorporating all tunnel and surface receivers). Variance based weighting for P- and S-wave first arrivals was set and RMS errors of 2.1 ms and 1.4 ms, respectively, obtained after 9 iterations. The final P-wave velocity model obtained using the joint trav-eltime tomography, along with the tunnel model and models of different fracture systems obtained from the previous studies (Berglund et al., 2003), are shown in Figure 5.9.

Figure 5.9. P-wave velocity model (RMS=2.1 ms) obtained from joint first arrival tomography with tunnel model and models of different fracture systems obtained from previous independent site investigations. (a) P-wave velocity model with aerial photo projected on top of the elevation model with red points indicating positions of different tunnel and surface receivers, tunnel model and arrows pointing where the tunnel intersects different fracture systems. P-wave velocity model with (b) tunnel model and models and surface intersections of the EW-3, (c) EW-3 and NE-1, and (d) EW-3, NE-1 and NNW-3 fracture systems.

The velocity model shown in Figure 5.9 indicates a good correlation with previous independent studies showing low velocity anomalies where the fracture systems are intersected and previously inferred. This is particularly true for the EW-3 system shown in Figure 5.9b, with a clear steeply dipping low velocity anomaly. Low velocity anomalies can also be associated with other mapped fracture systems (NE-1 and a minor NNW-3), however, not as constrained as in the case of the EW-3. Whether this is due to source-receiver pairs favoring more the EW-3, or a fractured zone bounded by the NE-1 and EW-3 remains unclear. Nonetheless, low velocity anomalies in the zone where the two are intersected can be seen, along with others suggesting the possibility of other fracture systems not inferred in the previous studies.

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A more localized analysis of the landstreamer-recorded data was addi-tionally conducted to analyze the seismic response of the NE-1 fracture sys-tem. For this purpose, the analysis was restricted to source gathers recorded with the landstreamer and all source stations located 200 m before, along the landstreamer, and 200 m after it. Only source gathers with good S/N ratios were used and the noisy traces excluded from the analysis, which resulted in a reduced dataset containing 150 source points and only the landstreamer recorded data. To obtain more constrained velocities along the landstreamer covered portion of the tunnel, the 200 m long streamer was separated into 7 zones. These 7 zones correspond to host rock before the NE-1 (HR-1), three sets of the NE-1 (NE-1-I, II and III) separated by two host rock segments (HR-2 and 3), and the host rock following the NE-1-III fracture set. The width of every zone corresponds to its width as intersected in the tunnel. The landstreamer-recorded data were subdivided into the same 7 zones by as-signing the corresponding receivers and picked P- and S-wave first arrivals to the zone where they were located. Following this, for every zone a linear regression analysis was done by fitting a line in the least-square sense to the picked first arrivals. The procedure was repeated for all the shots and the estimated velocities of all shots for the 7 zones mentioned are shown in Fig-ure 5.10. To show the data variability, the results are shown as box plots.

Figure 5.10. Estimated (a) P-wave and (b) S-wave velocities using linear regression analysis within 7 zones corresponding to host rock before and after the NE-1 (HR-1 and HR-4), three fracture sets if the NE-1 (NE-1-I to III) and the host rock segments (HR-2 and HR-3) separating the NE-1-II from its neighboring sets.

All 7 zones shown in Figure 5.10 indicate a characteristic P- and S-wave velocity signature. Host rock HR-1shows high velocities, as would be ex-pected for the intact host rock, while the HR-2 shows slightly lower veloci-ties than the former. This is likely an influence of the EW-3 fracture system situated at the end of the landstreamer. Compared to the HR-1, all zones show a velocity decrease, with P- appearing more affected than the S-waves, especially in the HR-3 zone. The velocity changes within the HR-2 and HR-3 may correspond to different intensities of fracturing, since both are de-scribed as fractured host rock (Berglund et al., 2003; Rhén et al., 1997).

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Due to the importance of elastic property estimation for engineering purpos-es, the Vp/Vs ratio and dynamic Poisson’s ratio were also calculated (Barton, 2007). To obtain the ratios, two approaches were used. According to Geldart and Sheriff (2004), the traveltime ratio of S- and P-wave direct arrivals for the same receiver corresponds to its Vp/Vs ratio. This was used to obtain the Vp/Vs and dynamic Poisson’s ratio for every landstreamer station. For the calculation purpose, the same reduced dataset was used and the results ob-tained shown in Figure 5.11a,b.

In addition to the aforesaid, the velocities obtained from the regression analysis (Figure 5.10) were used to obtain the ratios within same 7 zones, with the results shown in Figure 5.11c,d.

Figure 5.11. Dynamic elastic properties changes in the vicinity of the NE-1 fracture system obtained with two different approaches. (a) Vp/Vs and (b) dynamic Poisson’s ratio obtained as traveltime ratios for every receiver and 150 source points used for the analysis. (c) and (d) represent the Vp/Vs and dynamic Poisson’s ratios, respec-tively, within the 7 zones. Also shown are the widths of the individual fracture sets and the host rock segments separating them as encountered in the tunnel, along with the receivers within each of the zones. HR-1 and 4 represent host rock before and after NE-1, respectively, while HR 2 and 3 are the host rock segments separating the NE-1-II from its neighboring sets.

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As an indication of the data variability, box plots were used with the red lines and numbers inside a blue box representing the median value of a zone or a receiver. Although the estimated seismic wavelengths are on the order of 20–25 m, a distinct signature of all fracture sets of the NE-1, along with the host rock separating them, can still be noted. NE-1-II fracture set shows the most prominent drop of all parameters, potentially indicating a transition from an environment with low or no fluid conductivity to a highly fluid con-ductive environment (Berglund et al., 2003; Rhén et al., 1997). This distinct drop spatially coincides with the strong P-S and S-P wave mode conversions observed in the real data and supported by the modeling studies. However, due to the relatively large seismic wavelength, this decrease is likely an av-erage of the NE-1-II and its neighboring host rock segments (HR-1 and 2).

To quantitatively estimate the influence of different hydraulically conductive fractures on the attenuation of a passing seismic wave, seismic Q (inverse of attenuation) was calculated for the same 7 zones as shown in Figures 5.10 and 5.11c,d. The Q was estimated in the time domain, using a linear regres-sion approach and the amplitude ratios of the same seismic events recorded on the neighboring receivers (Tonn, 1991). The same reduced dataset was used again and Q estimated from both P- and S-wave first arrivals. Box plots shown in Figure 5.12 indicate the Q values for the 7 zones as used for previ-ous analyses for P- (Figure 5.12a) and S-wave (Figure 5.12b).

Figure 5.12. (a) Variation of the P-wave seismic quality factor (Qp); and (b) S-wave seismic quality factor (Qs) within the three fracture sets of the NE-1 (NE-1-I to III) and host rock segments (HR-1 to 4). To estimate Q, median P- and S-wave veloci-ties from Figure 5.10 were used, along with the dominant frequencies as observed in the data. Red numbers in the blue boxes represent median values.

Low Q values for the NE-1-II and the neighboring host rock zones (HR-2 and 3) indicate that these zones act highly attenuatively on both P- and S-wave. Host rock segments before and after the fracture system (HR-1 and 4) show high Q values, suggesting more competent rocks. NE-1-III, the highly hydraulically conductive set of NE-1, appears less attenuative for both P- and S-waves than the other fracture sets, or the majority of the host rock segments.

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5.2.2 Conclusions A surface-tunnel-surface seismic experiment was conducted at the Äspö Hard Rock Laboratory in southern Sweden. Here, the landstreamer was lo-cated inside the tunnel, along with planted 10 Hz vertical geophones and wireless seismic recorders on the surface. Compared to strong electric/EM noise contamination observed on geophone-recorded data, landstreamer data shows no traces of it, demonstrating its insensitivity to these types of noise. A combination of planted geophones and the landstreamer inside the tunnel, along with wireless units on the surface, enabled simultaneous recording of the seismics wavefield on both. Strong P- and S-wave first arrivals were conspicuous in the data, hence they were picked and used for joint P- and S-wave first arrival tomography. The obtained P-wave velocity model corre-sponds relatively well with the known steeply dipping fracture systems tar-geted from the survey design, and indicates others previously unknown.

Two large-scale, steeply dipping fracture systems, indicted strong mode-converted direct and reflected P- and S-wave energy on the source gathers in their vicinity. Both 3-D ray tracing reflection traveltime modeling and 2D finite difference modeling suggest that P-S and S-P energy conversion from the two is possible.

Noticeable delays of both P- and S-wave first arrivals were seen on the landstreamer recorded data, associated with one of the two mentioned frac-ture systems. These delays, along with picked P- and S-wave first arrivals, were used to estimate P- and S-wave velocities and their quality factors (Vp, Vs, Qp, Qs), along with Vp/Vs and dynamic Poisson’s ratios. Since the frac-ture system consisted of three differently hydraulically conductive sets sepa-rated by host rock, the parameters were estimated for different zones corre-sponding to either a fracture set or a host rock zone. The results indicate that the different hydraulic conductivity of fractures causes a noticeable signature on all parameters analyzed. The fracture system with highest degree of hy-draulic conductivity appears the least attenuative for both P- and S-waves and shows high values of both ratios analyzed, and lower S-wave velocity than its neighboring sets. The low and non-conductive fracture sets appear more attenuative and show a distinct decrease of all parameters analyzed.

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5.3 Paper III: Multi-component digital-based seismic landstreamer and boat-towed radio-magnetotelluric acquisition systems for improved subsurface characterization in the urban environment Two acquisition systems were developed within the sub-project TRUST 2.2. One is a boat-towed RMT (radio-magnetotelluric) system (Bastani et al., 2015; Mehta, 2017; Wang et al., 2017), while the other one is the seismic landstreamer discussed in this thesis. Although the paper focuses on intro-ducing both systems to a broader audience, I will focus only on the land-streamer portion of it. To test the landstreamer capabilities at another urban site, a seismic survey was conducted in Kristianstad, southern Sweden. The site hosted a chemical cleaning facility from early 1900s till late 1980s and during its operation an unknown amount of chlorinated hydrocarbons leaked into the subsurface (Johansson et al., 2017). Soil analysis conducted at the site showed high concentrations of chlorinated hydrocarbons (tetrachloro-ethylenes or PCE’s), that were used as a part of the chemical cleaning pro-cess (Johansson et al., 2017). Tetrachloroethylenes are considered as highly harmful and carcinogenic (Guha et al., 2012), and a danger exists that they might spread from the site towards a nearby UNESCO biosphere reserve, or infiltrated into the glauconite aquifer used for regional water supply (Johans-son et al., 2017).

5.3.1 Summary To map subsurface geological features that may be used as potential migra-tion pathways for the tetrachloroethylenes, two seismic profiles were ac-quired. From a geological perspective, the site consists of 5-20 m thick tills and clays overlaying a limestone layer of average thickness of 80 m, sitting on top of a glauconite aquifer.

Both seismic profiles were acquired using a combination of the seismic landstreamer and 1C wireless recorders connected to 10 Hz vertical geo-phones. At the time of acquisition (April 2014), the landstreamer consisted of 4 segments. Three segments had 20 sensors spaced 2 m each, while the fourth one had 20 sensors spaced 4 m. A seismic source similar to ”Betsy seismic gun” (Miller et al., 1986), charged with 12 mm blank cartridges was used with a source station spacing of 4 m shot along the landstreamer length. Due to existing site infrastructure, along with a nearby river, a variable num-ber of wireless units and spacing per seismic profile were used. This resulted in an approximately 400 m long Profile 1 and a 200 m long Profile 2. Loca-tion of the site, positions of the seismic profiles and a field photo showing the landstreamer deployed along a bicycle road with wireless units in its tail is shown in Figure 5.13.

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Figure 5.13. Seismic survey conducted in Kristianstad, southern Sweden. (a) Loca-tion of the two seismic profiles with position of wireless seismic recorders, existing site infrastructure, along with the nearby river and a UNESCO reserve. (b) Field photo showing the landstreamer and wireless recorders in its tail.

The Sercel LiteTM system (operating on GPS time) was used to record the data with a 1 ms sampling rate and 5 s long records. Data analysis was fo-cused only on the vertical component of the landstreamer, after merging it with the data recorded using wireless recorders, based on the common GPS time of the records. Both first arrival refraction tomography and reflection seismic processing were used to image the subsurface structures.

P-wave first arrival tomography was done using the ps_tomo code (Tryggvason et al., 2002) with cell sizes of 2 m in the inline and depth direc-tions and a wide cell in crossline direction to obtain a 2D velocity model. After 8 iterations, approximately 3 ms RMS errors were obtained for both profiles and the results shown in Figure 5.14.

Figure 5.14. P-wave first arrival traveltime tomography results along both profiles with survey elements and an aerial photo projected on top of the elevation model. (a)Velocity model along Profile 2. (b) Velocity model along Profile 1 with red ar-rows indicating potential fractures and black line drilled depth to bedrock. (c) An enlarged view of both profiles indicating undulated bedrock topography and poten-tial weakness zones.

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Figure 5.14 indicates a well delineated, highly undulating bedrock topogra-phy. No major low-velocity zones that would suggest a fracture or a weak-ness zone along the tomography model of Profile 2 can be noted. Two zones along Profile 1 show a significant velocity decrease in the velocity model, indicating fractures or weakness zones that may be used for contaminant migration.

In addition to tomography, P-wave reflection seismic processing was also conducted along both profiles with the final seismic sections shown in Fig-ure 5.15.

Figure 5.15. Processed reflection seismic sections with survey elements and an aerial photo projected on top of the elevation model. (a) Final migrated section along Pro-file 2. (b) Final migrated section along Profile 1 with red bar indicating drilled depth to bedrock and arrows pointing at a reflector discontinuity. (c) An enlarged view of both profiles with arrows indicating at a potential fracture or a weakness zone.

Stacked sections along both profiles indicate a well-delineated bedrock and show some discontinuities along the reflectors. A strong bedrock reflector dipping towards the river confirms the tomography results. Along Profile 2, reflector discontinuities are notable, but with no support from the tomogra-phy model, or other information, it is difficult to interpret them as geological features. Profile 1, on the other hand, shows clear reflector discontinuity (shown by the red arrow in Figure 5.15c), supporting the low velocity zone observed in the tomography model and further indicating the existence of a fracture or a weakness zone in the limestone bedrock.

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5.3.2 Conclusions To support the urban underground infrastructure planning projects and vari-ous near-surface applications, two data acquisition systems were developed at Uppsala University within the frame of TRUST 2.2. Both systems were introduced and their properties discussed and analyzed on two case studies. Since the focus of my thesis is on the seismic landstreamer, only the case study related with it, was discussed here.

The seismic landstreamer was used at a site contaminated with cancero-genic tetrachloroethylenes and two seismic profiles acquired to image poten-tial subsurface migration pathways of the contaminant. Only the vertical component of the landstreamer was analyzed and both first arrival tomogra-phy and reflection seismic processing used for data handling.

Both results show a well-delineated, undulated bedrock dipping towards a nearby river. Large low-velocity zone is notable on the tomography model along one of the profiles suggesting a possibility of either a fracture or a weakness zone. This is also supported by a break in the reflector continuity on the migrated seismic section of the same line. Results along the second line are less conclusive.

The results shown demonstrate the landstreamer’s ability to resolve shal-low subsurface structures and further illustrate its potential for urban and near-surface applications.

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5.4 Paper IV: 3C seismic landstreamer study of an esker architecture through shear- and surface-wave imaging To exploit the 3C nature of the developed landstreamer for shear-wave re-flection seismic imaging, and test its capabilities for surface-wave analysis, an earlier acquired dataset was revisited. The dataset was designed and ac-quired to maximize the seismic energy and data coverage of the vertical component. Goals of the survey were to image an esker architecture using P-wave refraction and reflection seismics for positioning of water infiltration wells feeding a managed aquifer recharge (MAR) plant (Maries et al., 2017). The MAR plant supplies with water 300,000 inhabitants of Turku city (SW Finland) and its region. Compared to the P-wave refraction and reflection results shown in Maries et al. (2017), this study focuses only on one seismic profile (Line 2). Along Line 2, in this study the horizontal crossline (trans-verse, SH-wave) was analyzed to provide SH-wave reflection sections. In addition to the former, the strong surface-wave nature on the vertical com-ponent was utilized to obtain shear-wave and Vp/Vs ratio distribution in the top 40 m using an MASW (multichannel analysis of surface waves) ap-proach.

5.4.1 Summary Seismic data analyzed in this study were acquired at the Virttaankangas site in SW Finland. Location of the site and seismic profile analyzed are shown in Figure 5.16a. Geology of the site consists of igneous and metamorphic bedrock overlain by the Virttaankangas esker complex (Mäkinen, 2003). Within the esker complex, 5 units of variable thickness with coarse-grained esker core and glaciofluvial fan sediments deposited successively can be separated, as illustrated in Figure 5.16b.

The data were acquired using a combination of 4 segments of the land-streamer (July 2014) and 51 wireless seismic recorders. The streamer had 3 segments with 20 units spaced 2 m and 1 segment with 20 sensors spaced 4 m. The wireless units were distributed along a 1 km long line with 20 m unit spacing. A 500-kg vertical drop hammer (Place et al., 2015; Sopher et al., 2014) was used as the seismic source with a large metal plate mounted at the bottom of the hammer casing to improve source to ground coupling. Starting from the first wireless unit, the 200 m long landstreamer was deployed and the source points 4 m spaced along its entire length acquired. At every shot location, the falling weight was released 3 times on the base plate. The indi-vidual hits were later used for vertical stacking and improving the S/N ratio. Compared to the acquisition approaches shown in Chapter 3 (Figure 3.2a), after acquiring all source location along the streamer length, the streamer

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was pulled forward without leaving any segment as an overlap with a previ-ous position. This was done due to survey design targeting the vertical com-ponent, with the wireless units enabling constant data coverage along the entire line.

Figure 5.16. (a) Location of the site and seismic profile analyzed with site geology indicated and yellow dots representing selected boreholes. (b) Illustration of differ-ent units comprising the esker complex of the site.

To acquire the data along the planned line length of 1 km, the streamer was moved 5 times and the entire acquisition took one day.

Although the source used is of a typical vertical-type nature, peculiarly, clear hyperbolic events were conspicuous on the horizontal crossline (trans-verse, SH-wave) component. The events were investigated by side-by-side comparisons versus the other two components (vertical and horizontal inline - radial), hodograms and using 2D finite difference modeling. Figure 5.17 shows side-by-side comparison of source gathers for the same source loca-tion of the landstreamer’s individual components, raw and after filtering.

Inspecting the Figure 5.17a,b,c, we can notice that the hyperbolic event shown by the red arrows appears strongest on the transverse component. Minor signature might be seen on the horizontal crossline, while the vertical component shows no traces of it. After some basic processing, the hyperbol-ic events is no longer evident on vertical and radial component, while it is significantly enhanced on the transverse component (Figure 5.17d,e,f). Note that, due to 51 wireless recorders connected to 10 Hz vertical geophones, the vertical component has 131 channels in total.

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Figure 5.17. Raw and processed source gathers after separation of the 3C land-streamer data into individual components and merging the vertical component with wireless seismic recorders, with the corresponding amplitude spectra. (a) Vertical component of the landstreamer with wireless recorders data merged – raw data. Raw data of the landstreamer’s (b) radial and (c) transverse components. (d) Processed source gathers of the landstreamer’s vertical component merged with wireless re-corders data. Processed source gathers of radial (e) and transverse (d) component of the landstreamer. Blue arrows indicate a P-wave bedrock reflection, while the red arrows indicate at what appears as an SH-wave bedrock reflection.

To validate if the hyperbolic event shown with red arrows in Figure 5.17f might be an SH-wave bedrock reflection, 2D finite-difference modeling, both acoustic and elastic were employed (Juhlin, 1995). Both the vertical and transverse component of the seismic data were analyzed to obtain P- and S-wave velocities down to bedrock. P-wave stacking velocities obtained from Maries et al. (2017) were used to represent P-wave bedrock and overburden velocities (800 m/s and 5000 m/s, respectively). For the S-wave, a moveout velocity of the event in the transverse component was used as the overbur-den velocity and an average value of shear-wave velocity for igneous-metamorphic bedrock (300 m/s and 3000 m/s, respectively). Drilled depth to bedrock of 48 m in that portion of the seismic profile was used as the bed-rock depth in the model (borehole VI282, Figure 5.16). Elastic modeling was

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done with the aforementioned parameters and a Ricker wavelet with a center frequency of 60 Hz, corresponding to the dominant data frequency. Since the SH-wave does not convert to other modes, acoustic modeling was conducted by setting the aforementioned shear-wave velocities as P-wave velocities and setting the shear-wave velocities to zero (Vp=300 m/s, Vs=0 m/s and Vp=3000 m/s, Vs=0 m/s). For traveltime matching purposes, this approach may be considered valid. For both modeling scenarios, cell sizes in the inline and depth directions were 0.5 m, absorbing boundary conditions on the side, a free-surface condition on the top and zero attenuation. A side-by-side comparison of the processed shot gather of the transverse component versus elastic and acoustic modeling result is shown in Figure 5.18.

Figure 5.18. Processed shot gather of (a) the transverse component of the land-streamer in comparison with (b) elastic and (c) acoustic finite difference modeled shot records. Note the matching time of the SH-wave reflection of interests shown by red arrows in real and synthetic gathers. Blue arrows indicate at a P-wave bed-rock reflection, matching well with the same event indicated in Figure 5.17a.

To further verify the SH-wave nature of the reflection shown by the red ar-rows in Figures 5.17c,f and 5.18, analysis of the particle motions (hodo-grams) was conducted with the results of several traces analyzed shown in Figure 5.19. The hodogram analysis was done on a 3C source gather (before separating the individual components of the landstreamer) from the same location as shown in Figures 5.17 and 5.18. All the wireless units were ex-cluded from the analysis. A window around the reflection of interests was taken to represent the shear-wave (green window), while the windows around P-wave first breaks (red windows) were taken as a representative of P-wave polarization. The results from traces analyzed suggest a pure shear (SH-wave) nature of the reflection of interest with angles between P- and S-waves from 75° to 105°. Both particle motions and principal component analysis indicate the event of interest in the transverse component to be or-thogonal to the other components, further supporting the SH-wave nature.

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Figure 5.19. Hodogram analysis of different traces showing S-wave (green line) and P-wave (red line) particle motions in different planes. Also shown and calculated are P- and S-wave polarization azimuths and angles between the two. P-wave first arri-vals (red boxes) were used to represent P-wave polarization, while the window around the reflection of interest (green box) was used as a representative of the shear-wave polarization. Blue and black dashed are the average particle motions computed using principal component analysis in different planes for P- and S-waves, respectively. Vertical versus transverse particle motions are nearly perpendicular, as would be expected if the reflection shown with red arrows in Figures 5.17c,f and 5.18 is of SH-wave nature.

After ensuring the SH-wave nature of the reflection of interest reflection seismic processing of the transverse component was conducted and a final stacked section produced. Figure 5.20 shows the result of the SH-wave re-flection processing. Since the SH-wave reflectivity could be seen only in the SW part of the profile, the processing was focused on the first 450 m of the total profile length. The SH-wave stacked section shows a more consistent bedrock reflectivity compared to the P-wave results shown in Maries et al (2017). Weak reflectivity patterns that may be connected with the morpho-logically undetectable kettle hole structures (MUKH; shown with yellow

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arrows) can be observed. A relatively coherent bedrock reflection matches well bedrock depth observed in the VI282 borehole and indicates shallower bedrock in the southwestern part of the profile.

Figure 5.20. Processed SH-wave (transverse component) reflection seismic section. Red bar indicates drilled depth to bedrock and yellow arrows weak reflectivity likely connected with the MUKH structure. Note the coherent bedrock reflection. Green boxes are receiver and red dots source loactions.

To test the landstreamer’s potential for MASW purposes and support the interpretation reported by Maries et al. (2017), surface-wave analysis on the vertical component of the steamer, after merging with the wireless data, was also conducted. The merged dataset was selected to obtain a constant mid-spread distribution along the entire profile. Since no overlap with previous and next streamer position was used, this introduced gaps in the edges of every steamer position. Since the spread design was not optimized for MASW purpose, several preprocessing steps had to be made to make the data suitable before applying standard MASW steps (Foti et al., 2017a; Iva-nov et al., 2008; Miller et al., 1999; Park et al., 1999a). The initial step in-volved restricting the merged landstreamer and wireless data to source gath-ers with maximum 5 wireless units (90 m distance) following the first and last landstreamer station. This step provided approximately 90 m overlap between succeeding streamer positions, for both positive and negative source-receiver offsets. To satisfy the horizontally traveling plane-wave criteria (Park et al., 1999; Foti et al., 2017), account for the near-field effect and suppress source noise, the next step included omitting the receivers with offsets less then ±15 m from the analysis. Following this, the dataset was separated into two subsets, one having only positive, and the other negative offsets. The two subsets were used for transformation into phase velocity – frequency dispersion images, which enabled an almost constant distribution of mid-spread positions. Analysis of both subsets showed the presence of only the fundamental mode, which was picked and the resulting dispersion curves jointly inverted to obtain a shear-wave velocity distribution along the profile.

The inversion was done by setting the half-space depth of about 40 m, a 10-layer model with progressive thickness, fixed density of 1900 kg/m3 and a Poisson‘s ratio of 0.35. Only the fundamental mode was used for the inver-

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sion since no other mode could be distinguished in the data. Every picked dispersion curve was inverted to obtain corresponding 1D shear-wave ve-locity profiles. Maximum number of iterations allowed was 10, with an av-erage RMS error of 2% after approximately 5 iterations.

To plot the data as a 2D shear-wave velocity distribution, all the 1D pro-files obtained from the inversion were interpolated in Matlab using nearest neighbor interpolation with the results shown in Figure 5.21a. Figure 5.21b shows the overlay of these velocities on top of the P-wave stacked section from Maries et al. (2017). Figure 5.21c shows the SH-wave stacked section with surface-wave obtained shear-wave velocities on top. Figure 5.21d shows the Vp/Vs ratio variation along the entire profile. P-wave tomography results from Maries et al. (2017), along with shear-wave velocity obtained from surface wave analysis, were used as input for the ratio calculation. Fig-ure 5.21e shows the Vp/Vs ratio overlaid on top of the interpreted P-wave reflection section by Maries et al. (2017).

Figure 5.21. MASW obtained shear-wave velocities in the top 40 m (a) with bore-hole VI282 stratigraphy and drilled depth to bedrock on other boreholes. (b) P-wave stacked section from Maries et al. (2017) with the surface-wave obtained shear-wave velocities on top. (c) SH-wave stacked section with the same shear-wave velocities and VI282 stratigraphy. (d) Vp/Vs ratio distribution along entire profile with VI282 stratigraphy and other boreholes showing drilled depth to bedrock. (e) Overlay of the Vp/Vs ratio on top of interpreted P-wave section by Maries et al. (2017).

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Although the SH-reflectivity is absent in the NE part of the profile, the sur-face wave obtained shear-wave velocities show a good match with depth to bedrock, based on the boreholes in that portion of the profile (Figure 5.21a). However, they did not penetrate down to the bedrock in the SW part of the profile. Nonetheless, they confirm the shallower bedrock nature in the NE and deeper in the SW part and match well with the stratigraphy of the site, as indicated by the borehole VI282. An excellent match between the P- and SH-wave reflectivity seen on the stacked section (Figure 5.21b,c), with the surface wave obtained shear-wave velocities is also observed. The Vp/Vs ratio distribution along the profile and its overlay on top of the interpreted P-wave section from Maries et al. (2017) is shown in Figure 5.21d. The Vp/Vs ratios show an excellent match with the stratigraphy indicated by VI282 with a clear signature of two top sand layers, water saturated and unsaturated layers and high ratios for the bedrock. The interpreted water table, structures related to MUKH, esker core, and proximal and distal fan lobes by Maries et al. (2017) are confirmed by the Vp/Vs ratio distribution.

5.4.2 Conclusions To exploit the 3C nature of the developed seismic landstreamer, and test its potential for MASW purposes, an earlier reported landstreamer study was revisited. The reported study dealt only with the P-wave refraction and re-flection analysis, while this study focuses on the SH-wave component of the same dataset. Apart for this, to support the interpretation conducted on the P-wave section, surface-wave analysis was conducted to obtain the shear-wave velocity and Vp/Vs ratio distribution along the entire profile. Although the seismic source used was of vertical-type nature, clear reflec-tions were conspicuous on the SH-wave component and their nature ana-lyzed. The analysis included a side-by-side comparison with other land-streamer components, particle motions analysis and finite difference model-ing using the velocities extracted from the seismic data and drilled depth to bedrock. Results of all analyses show a pure SH-wave nature of the reflec-tions. Following this, refection seismic processing of the SH-wave compo-nent was done with the stacked section showing well-delineated bedrock surface matching the existing boreholes. In addition to the bedrock reflec-tion, weak reflections correlating well with the glacial sedimentation history of the site are also notable.

Apart from this, surface-wave analysis was conducted using an MASW approach. Due to spread design limitations, the MASW was conducted on the vertical component data. Surface wave obtained shear-wave velocities show an excellent match with both P- and SH-wave reflectivity and correlate well with borehole based site stratigraphy. The surface-wave obtained shear-wave velocities, along with the P-wave first arrival tomography from the earlier study were used to obtain the Vp/Vs ratio distribution along the pro-

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file. The Vp/Vs ratios match well with the borehole based site stratigraphy and support the interpretation conducted in an earlier study.

The results shown in this study indicate that shear-wave imaging using verti-cal impact sources is possible, with a relatively good quality SH-wave stacked section produced. Furthermore, they illustrate the potential of the landstreamer for MASW purposes and show why 3C data acquisition for near-surface applications is necessary.

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6 Conclusions and outlook

To support the planning of underground infrastructure projects in urban en-vironments, and various other near-surface applications, a multicomponent seismic landstreamer was developed within the scope of this thesis. In the papers making the main part of my thesis, I have presented different studies demonstrating its technical advantages over conventionally available seismic acquisition systems. Apart from the technical parts, the papers deal with practical problems of interests to both the local communities where the data were acquired, and general scientific community on the potential of the streamer for various near-surface applications.

In comparison to conventional seismic surveys where the receivers are “planted”, the usage of landstreamer decreases the acquisition time, hence reduces the survey cost, and increases the overall efficiency. To this date, acquisition rates of up to approximately 1000 m per day of high-resolution (2-4 m shot and receiver spacing) seismic data have been achieved. Aside from the increased efficiency, technical properties of three-component digi-tal (micro-electro-mechanical systems - MEMS) sensors that the landstream-er was built with, offer numerous advantages. Some of these include broad-band data recording in one vertical and two horizontal components and digi-tal signal sampling and transmission. Digital sampling and data transmission make the selected sensors, therefore the landstreamer itself, insensitive to electric/electromagnetic noise contamination. Other advantages over com-mercially available landstreamer’s include the possibility of simultaneous data acquisition with both MEMS sensors and commonly used geophones, along with wireless seismic recorders of both types. The aforementioned technical specifications, along with others introduced earlier in my thesis and the overall streamer design have been scrutinized in studies presented in the papers.

In Paper I, the landstreamer recorded data showed higher quality and bet-ter signal bandwidth than 10 Hz and 28 Hz geophones tested. Comparison between the data acquired with the sensors mounted on the landstreamer and planted sensors of the same type showed no unwanted streamer induced effect on the overall data quality and only negligible differences. To test the electric/EM noise insensitivity of the landstreamer, and delineate bedrock level and inferred weakness zones within it, an urban study was conducted in Stockholm, Sweden. Two seismic profiles were acquired along one of the access tunnels of the Stockholm Bypass (Förbifart Stockholm), a 21-km long

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underground multilane highway. The landstreamer was combined with wire-less seismic recorders to obtain data coverage under a major road, without influencing the traffic regime. Although one of the seismic profiles was run-ning parallel to the tram tracks, no electric/EM noise was present in the data. First break traveltime tomography results along both profiles indicate a well-delineated bedrock level and show low-velocity anomalies coinciding with the previously inferred weakness zones.

The landstreamer was in Paper II combined with geophones in the Äspö HRL tunnel and wireless recorders on the surface. The unique acquisition geometry provided simultaneous data acquisition on all tunnel and surface seismic receivers. This combination enabled excellent data coverage for traveletime tomography and imaging of the rock mass between the tunnel and the surface. Obtained P-wave tomography model showed low velocities matching relatively well with known major fracture systems and indicated the possibility for the existence of others previously unknown. The unique acquisition geometry, with its high resolution and data redundancy, shows good potential for mining and other underground infrastructure planning applications. Data recorded with the geophones used in the tunnel show strong electric/EM noise contamination. This noise type is entirely absent on the landstreamer data, further demonstrating its insensitiveness to this noise type. The landstreamer was located in the portion where the tunnel intersect-ed a major fracture system consisting of three sets. The landstreamer data were further used to characterize the individual fracture sets and their host rocks with compressional and shear-wave velocities, seismic quality factors, Vp/Vs and dynamic Poisson’s ratios.

In Paper III, the landstreamer was used to image the subsurface and lo-cate potential migration pathways of a cancerogenic substance at a contami-nated site in Sweden. Two seismic profiles were acquired and both refraction tomography and reflection seismic imaging used for data handling of the landstreamer’s vertical component data. Results of both approaches on the two profiles showed a well delineated, relatively shallow, dipping bedrock. Both tomography and reflection sections indicated a possibility of a fracture or a weakness zone, suggested by other geophysical methods and drilling available at the site. This study illustrates the landstreamer’s potential for environmental related applications.

Paper IV focuses on exploiting one of the landstreamer’s horizontal components namely, the horizontal transverse (SH-wave) component and test the potential of the streamer for surface-wave data analysis. Although the seismic source used was of a typical vertical-type nature, the SH-wave component showed clear reflections. Processing of this component resulted in a relatively good quality SH-wave stacked section with well delineated bedrock surface and other reflections matching the glacial history of the site. Apart from this, a multichannel analysis of surface wave (MASW) approach was used on the vertical component data. The surface-wave obtained shear-

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wave velocities show an excellent match with the SH-wave reflectivity and borehole based stratigraphy of the site. Additionally, these shear-wave veloc-ities match well with P-wave reflectivity reported independently from the vertical component data. The surface-wave obtained shear-wave velocities, along with previously reported P-wave velocities (obtained through first break traveltime tomography), were used to obtain Vp/Vs ratio along the entire profile. The Vp/Vs ratios show an excellent match with the borehole based stratigraphy and water table depth. This study highlights the im-portance of multicomponent data recording for near-surface seismic studies, where the heterogeneous subsurface interacts with the seismic wave in a complex manner resulting in various seismic modes. Additionally, this is the first study that the landstreamer’s potential for MASW was illustrated, show-ing how different data handling results in a more constrained data interpreta-tion.

The studies presented in my thesis have demonstrated benefits of the de-veloped landstreamer and its advantages over conventional seismic acquisi-tion systems. The landstreamer was successful in imaging bedrock level, fractures and weakness zones in all studies shown. Its insensitiveness to electric/EM noise contamination was particularly demonstrated in Paper II, and the benefits and importance of multicomponent recording in Paper IV. Taken by Miller (2013): “one geophysicist’s noise is another’s signal”, along with claimed broadband signal of the landstreamer, surface-wave analysis was also done in Paper IV. The obtained results show the land-streamer’s potential for MASW studies and that the same dataset often con-tains useful information that may be extracted using different data handling techniques.

Although all the studies shown have successfully achieved the survey goals, they were primarily focused on the vertical component of the landstreamer. This, on the other hand, left the two horizontal components rather neglected. Therefore, the future efforts should aim at the development of a relatively light and portable P-, SV- and SH-wave seismic source that will enable the opportunity to fully exploit the landstreamer’s recording potential. The seis-mic wave interacts with the near-surface in a complex manner and for a complete representation of the seismic wavefield, multicomponent seismic sources and receivers are necessary.

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Summary in Swedish

Denna avhandling presenterar utvecklingen av ett seismiskt multikompo-nents- landstreamersystem som har använts vid undersökningar i stora infra-strukturprojekt såsom tunnelbyggen, men även vid flera andra ytnära till-lämpningar. I artiklarna som utgör huvuddelen av denna avhandling visas de tekniska fördelarna med landstreamersystemet jämfört med konventionella seismiska system. Utöver de tekniska delarna tar artiklarna även upp gene-rella vetenskapliga problem och möjligheter relaterade till användandet av landstreamersystem för ytnära tillämpningar, samt praktiska problem relate-rade till de lokala miljöer där data har inhämtats.

I jämförelse med konventionella seismiska mätningar där mottagare (geo-foner) planteras i marken är användandet av landstreamersystem mer effek-tivt och minskar tiden för inhämtning av data och därmed också den totala kostnaden för hela den seismiska undersökningen. Till dags dato, har en inmätningshastighet på upp till 1000 m per dag av högupplöst seismiskt data uppnåtts (2 - 4 m avstånd mellan mottagare samt mellan skottpunkter) . Utöver en ökad effektivitet i inmätningen erbjuder det digitala trekompo-nentssystemet baserat på MEMS-sensorer (Micro-Electro-Mechanical Systems) flera fördelar. Bland dessa kan nämnas bredbandsdatainspelning i en vertikal och två horisontella riktningar, men även digital sampling och data överföring. Den digitala samplingen och dataöverföringen gör varje enskild sensor, och därmed hela landstremersystemet, okänsligt för elektriskt och elektromagnetiskt brus. Landstreamersystemet erbjuder möjlighet att kombinera inmätning med MEMS-sensorer och traditionella geofoner längs ett kablat system och trådlösa sensorer av både MEMS-typ och konvention-ella geofoner. Detta ger ett seismiskt system med mycket stor flexibilitet för de flesta situationer. De tekniska detaljerna av ovan nämnda system har un-dersökts noga i flera av de studier som presenteras i artiklarna i denna av-handling.

I Artikel I, visade data inspelat med landstreamer-system bättre kvalité och bättre signalbandbredd än data från de 10 respektive 28 Hz-geofoner som också testades. Jämförelse mellan MEMS-sensorer monterade på strea-mer och likadana sensorer som planterats på traditionellt vis, visade endast försumbara skillnader och ingen oönskad streamerinducerad effekt kunde påvisas. För att testa streamern i urban miljö där systemet utsätts för elekt-riskt och elektromagnetiskt brus gjordes en undersökning i Stockholm. Mål med denna undersökning var också att mäta djup till bergrunden och uttyda

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eventuella deformationszoner i berget. Två seismiska profiler inmättes längs en av accesstunnlarna till Förbifart Stockholm. Förbifart Stockholm är en 21 km lång flerfilig motorväg som kommer gå i tunnlar förbi Stockholm. Land-streamersystemet kombinerades här med trådlösa sensorer för att få bättre datatäckning under en stor väg utan att påverka trafiken med avspärrningar. Trots att en av profilerna löpte parallellt med tågspår syntes ingen störning från elektriskt eller elektromagnetiskt brus i inspelat data. Seismisk P-vågstomografi längs båda profilerna visar en tydlig berggrundstopografi med låghastighetsanomalier (vilka kan orsakas av deformationszoner i berget) som sammanfaller med tidigare tolkade deformationszoner.

I Artikel II användes en kombination av landstreamersystemet och ett traditionellt kablat geofonsystem i Äspö HRL (Äspö Hard Rock Laboratory i Oskarshamn i södra Sverige) tillsammans med trådlösa sensorer ovan jord. Denna unika inmätningsgeometri erbjöd möjlighet att simultant mäta i tun-neln samt ovan jord med skottpunkter både ovan och under jord. Detta gav en utmärkt möjlighet, med bra datatäckning, att mäta berghastigheten i ber-get mellan tunneln och markytan. Den erhållna P-vågstomografiska hastig-hetsmodellen visade relativt god överensstämmelse mellan låghastighetszo-ner och tidigare kända deformationszoner, men indikerade även möjliga deformationszoner som inte varit kända sedan tidigare. Denna unika inmät-ningsgeometri med hög redundans gav en högupplöst hastighetsmodell av berget och visade på potentialen för gruv- och underjordsundersökningar med seismiska metoder. Tunneldata från traditionella geofoner uppvisade en kraftig elektrisk/elektromagnetisk brusnivå vilken var helt frånvarande på MEMS-sensorerna i landstreamern. Detta visade återigen på MEMS-sensorernas okänslighet för elektriska/elektromagnetiska störningar. Land-streamersensorerna var placerade i en del av tunneln där de korsade ett större deformationssystem. Sålunda kunde de individuella spricksystemen analyse-ras gällande P- och S-vågshastighet, Vp/Vs ratio, dynamisk Poisson's ratio och seismiska kvalitetsfaktorer.

I Artikel III användes landstreamern för att undersöka en kontaminerad plats, med bland annat ett cancerframkallande ämne i marken. Ett mål var att förstå hur kontaminationen skulle kunna migrera med grundvattnet under jord. Två mer eller mindre vinkelräta seismiska profiler inmättes på platsen. Både tomografisk- och reflektionsprocessering utfördes och båda metoderna visade på en svagt lutande berggrundsyta. Båda modellerna visade på en möjlig deformationszon som också indikerats med andra oberoende geofy-siska metoder. Denna studie illustrerar landstreams potential för miljörelate-rade applikationer.

Artikel IV fokuserade på att utnyttja en av de horisontella komponenter-na från landstreamersensorerna; den transversa S-vågen (SH), samt under-söka möjligheten för ytvågsanalyser av landstreamerdata. Trots att den seismiska källan var av vertikalimpakttyp, syntes tydliga reflektioner från SH-komponenten. Reflektionsprocessering av SH-komponenten gav en stack

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med god kvalité där berggrundsytan var avbildad och reflektioner som mat-chade glaciala avlagringar kunde urskiljas. Utöver detta analyserades ytvå-gorna (multichannel analysis of surface waves – MASW processering) med utgångspunkt från den vertikala komponenten. Hastighetsmodellen från yt-vågsprocesseringen matchar mycket väl P-vågsreflektioner och SH-vågsreflektioner samt borrhålsbaserad stratigrafisk tolkning. Vp/Vs ratio kunde beräknas utefter hela profilen med P-vågshastigheter från tomografi-modell och S-vågshastigheter från ytvågsprocesseringen. Vp/Vs ratio över-ensstämde mycket väl med stratigrafi och grundvattennivå. Denna studie visade tydligt vikten av multikomponentdata vid ytnära seismiska studier där heterogeniteten i marken interagerar med seismiska vågor på ett komplext sätt och resulterar i olika seismiska vågor. Detta är den första studien där MASW-processering illustrerades med landstreamerdata och den visar att olika dataprocesseringsmetoder i kombination kan ge en bättre och mer av-gränsad tolkning. Möjligheten att genomföra flera processeringsmetoder, såsom S- och P-vågsreflektion, tomografi och ytvågsprocessering med samma data kräver att seismiska mätinstrument med bredbandig multikom-ponent används.

Studierna som här presenteras i min avhandling visar på flera fördelar med den utvecklade landstreamern jämfört med konventionella seismiska mätsy-stem. I dessa studier har bergrundstopografi och potentiella deformationszo-ner kunnat identifieras och ofta bekräftats med andra geofysiska metoder eller med borrhål. Okänslighet för elektriska/elektromagnetiska störningar har visats särskilt tydligt i Artikel II, och fördelen samt vikten av multikom-ponentsdata demonstrerades i Artikel IV. Tack vare landstreamerns bred-bandssignal kunde ytvågsprocessering utföras på data från en ”vanlig” seismisk inmätning i Artikel IV. Jag vill nämna ett citat från Miller (2013): ”one geophysicist's noise is another's signal” (ung. ”en geofysikers brus är en annan geofysikers signal”). Resultatet visar på landstreamerns potential att mäta data som kan behandlas med flera olika processeringsmetoder och därmed ge en förbättrad möjlighet till en avgränsad tolkning.

Trots att alla studier uppnått de mål som var satta har de flesta studier fo-kuserat på den vertikala komponenten och P-vågsdata. Detta utelämnar de horisontella S-vågskomponenterna och den möjlighet som de kan erbjuda. Därför bör det fortsatta arbetet fokusera på att utveckla en lätt och portabel P-, SV-, och SH-vågskälla som kan erbjuda möjlighet att till fullo utveckla landstreamerns potential. De seismiska vågorna interagerar med heterogeni-teten i marken på ett komplext sätt och för att få en komplett bild av denna heterogenitet krävs ett seismiskt mätinstrument med flerkomponentsmotta-gare och en flerkomponentskälla.

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Acknowledgments

The PhD has been an exciting, enjoyable, fulling, challenging, stressful, occasionally frustrating and, most of all, a fun journey which I would have never managed without the help of many good people throughout the years.

First of all are my supervisors, Alireza Malehmir and Chris Juhlin. They gave me this privilege to be a PhD student in Uppsala and had patience for all my questions and comments. One was there to push me to go bigger then my own plans and ideas and explore more, while the other was there to give “a slight nudge out the door” when necessary. I’m truly thankful for all your help and feel honored to have been your student.

Would be difficult to reach this step and find all the joys geophysics does, and love for what I work with, without the help of two giants, Lars Dynesius and Hans Palm. I thank Lasse for all his help and discussions, and will keep Hasse forever in my memory.

It was so many others who were there to discuss, advise, help, talk, drink beer, dance, do sports, fieldworks, camping and other trips. It would be diffi-cult to number all the nice stuff we have shared together and I’m sorry in advance if I have missed someone. From geophysics and seismology groups, I thank Omid, Magnus, Emil, Monika, Sebastian, Shunguo, Georgiana, Remi, Daniel, Peter Hedin, Ruth, Silvia, Fred, Chris Hieronimus, Mahboubeh, Suman, Sahar, Magdalena, Azita, Laura, Michael and Michael, Tegan, Thomas, Laust, Peter Schmidt, David Gee, Angeliki, Karin, Darina, Bjorn, Bjarne, Pan, Ruixue, Fengjiao, Maria, Theo, Joakim, Mohsen, Clau-dia, Ari and Roland.

People that came into my life via PhD studies and whom I’m proud to call my friends. I thank Iwa, Franz, Jarek, Johanna, Gardar, Marta, Dragos, Christos, Joao, Rudi, Nada and Alicija. Sorry if I forgot someone Big thanks goes to Ruta for being patient with me and helpful in these few stress-ful months of thesis writing.

I thank Fatima Ryttare-Okorie for always being helpful, you made all the complicated procedures easygoing. The good people of SGU for welcom-ing me in their homes, helpful discussions and skills they shared. Thank you, Anna, Mehrdad and Stefan. Special thanks goes to Taher, Leif, Anna, Fred and Erik for their help with TGIF’s and many small and big things along the way.

I thank Maria Ask and all the TRUST people for excellent meetings, good work we have done together and the opportunities TRUST has brought.

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My old professors and colleagues from University of Belgrade, Faculty of Mining and Geology for teaching me to think outside the box. I thank Ilija Vasiljević, Branislav Sretenović, Snežana Ignjatović, Vesna Cvetkov, Dejan Vučković, Ivana Vasiljević, Dobrica Nikolić, Bane Sretković, Deki Milošev-ski, Aleksandar Đorđević, Marinko Toljić, Boban Marinković and Vladica Cvetković. Huge thanks goes to Ministry of Youth and Sports, Republic of Serbia for their support from my early Bachelor to late PhD days.

An enormous thank you goes to Magnus and Emil for their help with Swedish part of the thesis and proof reading of its parts.

I thank Ylva Forsberg, Sara Andersson and my family and friends back home in Serbia for believing in me and cheering me up in difficult moments throughout different stages of my PhD.

Last but not the least, I thank my opponent André, and the examination committee, Bea, Michal and Cedric for investing their time in reading the thesis and travelling to Uppsala for my big day.

Bojan Brodić, Uppsala, December 2017.

71

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